Lost in translation: IT business value research and resource complementarity—an integrative framework, shortcomings and future research directions
Abstract
EconStor is a publication server for scholarly economic literature, provided as a non-commercial public service by the ZBW.
Full text
Schweikl, Stefan; Obermaier, Robert Article — Published Version Lost in translation: IT business value research and resource complementarity—an integrative framework, shortcomings and future research directions Management Review Quarterly Provided in Cooperation with: Springer Nature Suggested Citation: Schweikl, Stefan; Obermaier, Robert (2022) : Lost in translation: IT business value research and resource complementarity—an integrative framework, shortcomings and future research directions, Management Review Quarterly, ISSN 2198-1639, Springer International Publishing, Cham, Vol. 73, Iss. 4, pp. 1713-1749, https://doi.org/10.1007/s11301-022-00284-7 This Version is available at: https://hdl.handle.net/10419/307260 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/
Vol.:(0123456789) https://doi.org/10.1007/s11301-022-00284-7 1 3 Lost intranslation: IT business value research andresource complementarity—an integrative framework, shortcomings andfuture research directions StefanSchweikl1 · RobertObermaier1 Received: 5 September 2021 / Accepted: 20 June 2022 © The Author(s) 2022 Abstract Despite longstanding research efforts, there is still ambiguity surrounding the business value created by IT. To approach this conundrum, research focus has progressed from an isolated investigation of IT to the assessment of complementarity between IT and different non-IT resources such as work practices or decision structures. However, incoherence around the characteristics and scope of these complementary non-IT resources has created a fragmented body of research, preventing a sustainable knowledge creation. Thus, in this paper we synthesize the dispersed research efforts, identify shortcomings in the extant literature, and derive opportunities for future research. Specifically, we present a converging definition of complementary non-IT resources and specify their role in the value creation process from IT by viewing it through three distinct lenses: microeconomic theory, resource-based view, and contingency theory. We structure current research efforts by organizing complementary non-IT resources into distinct categories, namely strategy, structure, practices, processes, and culture (organizational resources), top management support, internal relations, and external relations (relational resources), worker skill (non-IT human resources), non-IT physical resources, as well as internal funds and external funds (financial resources). Finally, we highlight five important shortcomings in the current literature, such as the predominant use of reductionist approaches or monolithic IT measures, and make actionable recommendations to resolve them. Keywords Literature review· Classification· IT value· Complementarity· Resource system· Configurations JEL Classification M15 * Stefan Schweikl stefan.schw[email protected] 1 Chair forBusiness Economics, Accounting andManagerial Control, University ofPassau, Innstraße 27, 94032Passau, Germany Management Review Quarterly (2023) 73:1713–1749 / Published online: 21 July 2022
S.Schweikl, R.Obermaier 1 3 1 Introduction In an era defined by rapidly growing information technology (IT) budgets, it has become paramount for IT executives to create business value from IT (Kappelman et al. 2021). In this context, IT business value (ITBV) is defined as “the organizational performance impacts of information technology at both the intermediate process level and the organization wide level, and comprising both efficiency impacts and competitive impacts” (Melville etal. 2004, p. 287). Yet, only some IT executives are able to accomplish this essential but elusive objective, as there is an increasing divergence in organizational performance across firms that adopt digital technologies (Andrews etal. 2016). Thereby, this dispersion appears to originate from the ability of some firms to exploit complementarities between IT and non-IT resources (Gal etal. 2019). Naturally, the successful deployment of any IT resource depends on the institutional context surrounding it, as it is embedded in a larger system of interoperating resources (Nadkarni and Prügl 2021). Thus, not only the IT resource itself, but also non-IT resources such as decision structures, worker skills, or supplier relations are pivotal to the successful implementation and utilization of IT (Kohli and Grover 2008; Wade and Hulland 2004). That is why the high rate of abandoned IT projects and the frequently reported inadequate return on IT investments—dating back to the Solow Paradox (Solow 1987)—are not necessarily solely attributable to the IT resource itself, but also to the non-IT resources it interacts with (Doherty etal. 2012; Schweikl and Obermaier 2020). A practical example that illustrates this point is the case of FoxMeyer, which was once the fourth largest distributor of pharmaceuticals in the US. Due to a lack of senior management support and a shortage of skilled workers, the implementation of an enterprise resource planning (ERP) system failed disastrously and ultimately contributed to the firm’s bankruptcy (Scott 1999). Hence, non-IT resources can affect the business value created from IT either by completing and thereby enhancing the performance effects or by suppressing some or all of the potential IT-related benefits (Brynjolfsson and Milgrom 2013). As a consequence, the importance of additional research on the interplay between IT and non-IT resources has been continuously emphasized (Kohli and Grover 2008; Melville etal. 2004; Wade and Hulland 2004), which has cumulated in the emergence of a large body of empirical studies. However, due to the variety of non-IT resources that may act as complements to IT, a fragmented and insulated body of empirical studies has emerged that is comprised of a wide range of different research areas such as strategic IT alignment (e.g. Chan etal. 1997), social alignment (e.g. Wagner etal. 2014), complementary investments to IT in work practices (e.g. Bresnahan etal. 2002), IT and decision structures (e.g. Andersen and Segars 2001), or IT-associated process-reengineering (e.g. Devaraj and Kohli 2000). Surprisingly, there is no comprehensive review that synthesizes and integrates these important but dispersed research streams to obtain a holistic view on resource complementarity in ITBV research. While Wiengarten etal. (2013) 1714
1 3 Lost intranslation: IT business value research andresource… reviewed the literature regarding complementary organizational resources, they did not consider human or relational aspects, although their pivotal role in the value creation process from IT has been explicitly highlighted (Grover and Kohli 2012; Powell and Dent-Micallef 1997). Further, scholars call for more research on the role of complementary non-IT resources in the value creation from IT (Chae etal. 2014; Piccoli and Lui 2014) as well as advocate for a classification of complementary non-IT resources to structure the research field and enable a sustainable knowledge creation (Kim etal. 2011). Thus, we seek to address these research needs and utilize the gained knowledge to translate shortfalls in our current understanding of resource complementarity into opportunities for future research (Rowe 2014). Consequently, we aim to answer the following research questions: (1) What is the role of complementary non-IT resources in the value creation from IT? (2) What complementary non-IT resources have been empirically investigated so far and how can they be categorized? (3) What are shortcomings in the current literature and how can they be resolved? To approach our research questions, we systematically reviewed 227 articles from a broad range of academic journals in the business field. In doing so, we make three important contributions to the ITBV literature: first, we present a converging definition of complementary non-IT resources. Second, we develop a systematic classification of complementary non-IT resources, including strategy, structure, practices, processes, and culture (organizational resources), top management support (TMS), internal relations, and external relations (relational resources), worker skill (non-IT human resources), non-IT physical resources, as well as internal and external funds (financial resources). Building on this classification, we also organize current empirical research efforts to obtain insights on the relationship between IT and specific non-IT resources. Third, we highlight five shortcomings in the existing literature and present actionable solutions to develop an agenda for future research efforts. In particular, we show that research has so far focused on reductionist approaches, leading to a major knowledge gap regarding different configurational recipes of IT and complementary non-IT resources that are sufficient to attain desired performance outcomes. The remainder of this article is structured as follows: in the next section, we present a definition and classification of complementary non-IT resources. In Sect.3, we outline the different theoretical lenses used to describe the role of complementary non-IT resources in the value creation process from IT and provide an integrative framework on complementarity in ITBV research. In Sect.4, we detail our systematic review process. In Sect.5, we organize empirical research efforts according to our classification of complementary non-IT resources and shed light on the complementarity of certain IT and non-IT resources. In Sect.6, we highlight shortcomings in the extant literature and suggest avenues for future research. In Sect.7, we make some concluding remarks. 1715
S.Schweikl, R.Obermaier 1 3 2 Conceptualizing complementary non‑IT resources inITBV research 2.1 Definition ofcomplementary non‑IT resources Two or more input factors or activities are complementary when “doing (more of) any one of them increases the returns to doing (more of) the others" (Milgrom and Roberts 1995, p. 181). Thus, the economic value generated by the combination of two or more complementary input factors or activities surpasses the value that would be created by utilizing them in isolation (Milgrom and Roberts 1990, 1994). Thereby, empirical evidence suggests that complementarities among heterogeneous resources are particularly powerful performance drivers (Ennen and Richter 2010). While it is possible to implement IT with minimal organizational changes, the successful introduction of an IT system is often associated with a fundamental organizational transformation (Hammer 1990). Thus, the success of an IT investment seems not only to depend on the investment itself, but also on the non-IT resources it’s surrounded by (Davern and Kauffman 2000). In this regard, a firm’s ability to create business value by combining IT resources with non-IT resources is referred to as IT complementarity (Masli etal. 2011). Although a variety of conceptual works have stressed the importance of complementary non-IT resources in the value creation form IT (Brynjolfsson and Hitt 2000; Cao etal. 2016; Kohli and Grover 2008; Melville etal. 2004; Wade and Hulland 2004; Wiengarten et al. 2013), there is still incoherence surrounding the concept of IT complementarity. While some studies have addressed organizational aspects (Clemons and Row 1991; Wiengarten etal. 2013), others have highlighted the importance of human resources (Brynjolfsson and Hitt 2000), and yet others focus on relational arrangements as a key piece to create value from IT (Grover and Kohli 2012; Kohli and Grover 2008). This diverging research focus has resulted in dissent on the scope and characteristics of complementary non-IT resources and lack of a converging definition that encompasses the varying resource dimensions (see Table1 for an overview of important conceptual works). Despite the long-standing ambiguity, hardly any new conceptual work has emerged in recent years to address this issue. Consequently, we approach this research need by devising a comprehensive definition of complementary non-IT resources based on established resource dimensions. Resources are generally seen as all assets, capabilities, knowledge, etc. within a firm (Barney 1991). Expanding this perspective, researchers have proposed that firm resources are also able to span organizational boundaries and are embedded in the relationships with external organizational partners (Lavie 2006; Zander and Zander 2005). Although firms do not possess resources outside of firm boundaries, they may be able to access and leverage some of them to enhance the value of intra-firm resources (Lavie 2006). Thus, it is not sufficient to solely consider resources within a firm, but also between firms, to achieve a more exhaustive view on IT complementarity (Grover and Kohli 2012). There are, however, environmental factors outside an organization that a firm has no influence on 1716
1 3 Lost intranslation: IT business value research andresource… Table 1 Overview of conceptual works on complementary non-IT resources (extension of Wiengarten etal. 2013) References Definition Classification of complementary non-IT resources Weill and Olson (1989) No explicit definition Strategy, structure, firm size, task, individual characteristics Clemons and Row (1991) No explicit definition Strategy, human capital, capital access, firm size Scott Morton (1991) No explicit definition Strategy, structure, processes, individuals and roles Henderson and Venkatraman (1993) No explicit definition Strategy, structure, policies, processes, worker skill Brynjolfsson and Hitt (2000) No explicit definition Strategy, structure, work practices, processes, culture, supplier and customer relations, worker skill Davern and Kauffman (2000) No explicit definition Strategy, policies, training, incentive systems, processes, management skill, knowledge sharing Dedrick etal. (2003) No explicit definition Structure, practices, training, process, organizational change, worker skill Melville etal. (2004) No explicit definition Structure, policies, workplace practices and rules, culture, relationships within and among firms, worker composition, non-IT physical assets, firm size Wade and Hulland (2004) No explicit definition Structure, culture, TMS, location, firm size Piccoli and Ives (2005) No explicit definition Structure, processes, culture, TMS, internal and external relationships, brand, physical assets, firm size Kohli and Grover (2008) No explicit definition Structure, policies, training, processes, culture, relationship assets, non-IT people and management Ennen and Richter (2010) No explicit definition Strategy, structure, policies, practices, processes, knowledge Cao etal. (2011) No explicit definition Strategy, structure, politics, process, culture Masli etal. (2011) No explicit definition Strategy, processes, culture, external relations Grover and Kohli (2012) No explicit definition Distribution capability, order-taking capability Wiengarten etal. (2013) “[…] non-IT resources within a firm that complement IT to affect organizational performance.” (p. 34) Strategy, structure, processes, culture Cao etal. (2016) No explicit definition Strategy, structure, operational aspects, processes, culture 1717
S.Schweikl, R.Obermaier 1 3 including government policies, national culture, legislation, or certain industry characteristics, which have to be delineated from the concept of intraand interfirm resources (Wade and Hulland 2004). Besides the intraund inter-firm setting, resources are often grouped into tangible and intangible ones (Barney 1991; Grant 1991). Tangible resources are generally visible and can be quantified. They include physical resources like machines, equipment, and the location of the firm as well as financial resources (Grant 1991). Intangible resources encompass immaterial assets and can be divided into (Grant 1991; Musiolik etal. 2012): (1) Organizational resources, which characterize the setting in which employees have to work and include structure, practices, culture, etc. (2) Relational resources, which reflect the relations within a firm and between firms. These include, for example, interactions between employees in different departments or customer relations. (3) Human resources, which are comprised of the skills, knowledge, and experience of employees. (4) Technological resources, which span non-physical assets such as business applications or databases. These resource dimensions can be further differentiated into those that pertain to IT resources and those that do not. Thereby, IT resources are comprised of technical IT resources including IT infrastructure like hardware assets (IT physical resources), business applications like an ERP system (technology resources), as well as human technical skills and IT managerial skills (IT human resources) (Melville etal. 2004). The remaining resources can in turn be categorized as non-IT resources and divided into organizational resources, relational resources, non-IT human resources, non-IT physical resources, and financial resources. In the light of this characterization of non-IT resources and the notion that complementarity between IT and non-IT resources amplifies the business value created by them (Milgrom and Roberts 1995), we define complementary non-IT resources as organizational resources, relational resources, non-IT human resources, non-IT physical resources, and financial resources within and between firms that magnify the impact of IT resources on organizational performance at the intermediate process level or organization wide level. 2.2 Classification ofcomplementary non‑IT resources Besides a definition of complementary non-IT resources, a granular classification of complementary non-IT resources must also be established in order to systematically analyze empirical results and gain insights regarding the existence of complementarities between IT and certain non-IT resources. Accordingly, we developed—based on a careful review of prior suggestions of complementary non-IT resources categories (see Table1) and an examination of studies that define specific resource categories common to all organizations (e.g., Chandler 1962; Mintzberg 1979)—a comprehensive classification of complementary non-IT resources (see Table2). In doing so, we further disaggregate complementary non-IT resources into the following distinct categories: (1) Organizational resources contain the business strategy of a firm (Chandler 1962), structure (Mintzberg 1979), practices (Gibson et al. 2007), processes (Davenport and Short 1990), and culture (Schein 1985), 1718
1 3 Lost intranslation: IT business value research andresource… Table 2 Categories of complementary non-IT resources Dimension Category Description References suggesting it as a complementary resource category to IT Organizational resources Strategy Strategy is the identification of a company’s long-term objective, adoption of courses of action, and allocation of resources required to accomplish these goals (Chandler 1962) Brynjolfsson and Hitt (2000), Cao etal. (2011, 2016), Clemons and Row (1991), Davern and Kauffman (2000), Ennen and Richter (2010), Henderson and Venkatraman (1993), Scott Morton (1991), Weill and Olson (1989) and Wiengarten etal. (2013) Structure Structure is the set of ways in which work is divided into different tasks to achieve coordination (Mintzberg 1979) Ennen and Richter (2010), Henderson and Venkatraman (1993), Melville etal. (2004), Piccoli and Ives (2005), Wade and Hulland (2004), Wiengarten etal. (2013) Practice Practices are rules, policies, programs, or systems that permit or promote certain types of behavior (Gibson etal. 2007) Brynjolfsson and Hitt (2000), Davern and Kauffman (2000), Dedrick etal. (2003), Ennen and Richter (2010), Kohli and Grover (2008), Melville etal. (2004) Process Processes are a set of defined activities or tasks to achieve distinct business outcomes (Davenport and Short 1990) Brynjolfsson and Hitt (2000), Ennen and Richter (2010), Henderson and Venkatraman (1993), Kohli and Grover (2008), Melville etal. (2004), Piccoli and Ives (2005), Scott Morton (1991), Wiengarten etal. (2013) Culture Culture reflects the shared values, ideals, and convictions of organizational members, which manifest themselves in their behaviour (Schein 1985) Cao etal. (2011, 2016), Kohli and Grover (2008), Melville etal. (2004), Piccoli and Ives (2005), Wade and Hulland (2004), Wiengarten etal. (2013) Relational resources TMS Top management support constitutes the degree of general support or commitment from top management (Igbaria etal. 1997) Piccoli and Ives 2005 Wade and Hulland 2004 Internal relations Internal relations refer to individuals, groups, or departments collaborating across intra-organizational boundaries Davern and Kauffman (2000), Melville etal. (2004), Piccoli and Ives (2005) External relations External relations reflect a firm’s relationships with external partners and its reputation or brand (Ray etal. 2013) Brynjolfsson and Hitt (2000), Grover and Kohli (2012), Kohli and Grover (2008), Masli etal. (2011), Melville etal. (2004), Piccoli and Ives (2005) Non-IT human resources Worker skill Worker skill reflects the qualifications or competence of employees not directly related or limited to their technical abilities (Bresnahan etal. 2002) Brynjolfsson and Hitt (2000), Dedrick etal. (2003), Kohli and Grover (2008) Non-IT physical resources Location, equipment, etc Physical non-IT resources are tangible assets that are not related to physical IT assets and used for producing goods, providing services, as well as the administration of the organization Melville etal. (2004), Piccoli and Ives (2005), Wade and Hulland (2004) Financial resources Internal funds Internal funds consist of existing liquidity and unused debt that can be borrowed at conventional interest rates (Chatterjee and Wernerfelt 1991) Clemons and Row (1991) External funds External funds are comprised of new equity and high-risk debt (Chatterjee and Wernerfelt 1991) Clemons and Row (1991) 1719
S.Schweikl, R.Obermaier 1 3 (2) relational resources can be further split into TMS (Igbaria et al. 1997), internal relations between individual, groups, or departments and external relations with other parties beyond organizational boundaries (Ray etal. 2013), (3) non-IT human resources reflect the worker skill not directly related or limited to technical abilities (Bresnahan etal. 2002), (4) non-IT physical resources contain material assets not related to physical IT assets, such as mechanical equipment (Melville etal. 2004), and (5) financial resources represent the access to internal and external funds (Chatterjee and Wernerfelt 1991). 3 Theoretical background andanintegrative framework ofcomplementarity inITBV research 3.1 Theoretical underpinnings used inresearch oncomplementarity inITBV Having outlined the characteristics and scope of complementary non-IT resources, the question still remains as to what role they play in the value creation process from IT. Researchers have applied several theoretical frameworks to answer this question, whereby three particularly prevalent theoretical lenses have emerged: microeconomic theory, resource-based view (RBV), and contingency theory (Oh and Pinsonneault 2007). Although, these theories are not mutually exclusive in many respects—as reflected by the fact that a variety of studies span multiple theoretical underpinnings (e.g. Schwarz etal. 2010; Tanriverdi 2005)—each has a different perspective on the mechanisms to create value from IT and the conditions under which ITBV emerges (see Table3). Therefore, we examine each theory to gain a more profound understanding on the role of complementary non-IT resources in the business value creation from IT. 3.1.1 Microeconomic theory On a firm level, the economic theory of production is generally applied to specify the contribution of different inputs to output. Inputs include non-IT capital and non-IT labor as well as IT capital and IT labor, whereas output is reflected by sales or sales per employee (labor productivity). Based on the assumption of a certain production function, the contribution of input factors to the output can be measured econometrically. Given this economic relation, IT is regarded as a technology that has a dual influence on productivity. On the one hand, IT can directly improve productivity via the automatization of business processes by increasing IT capital relative to labor input and, on the other hand, indirectly by facilitating the flow of information within and between firms. This entails the potential to more efficiently combine the different input factors by restructuring work flows and business processes (Dedrick etal. 2003). To assess the impact of IT on productivity, the gross marginal product, defined as the increase in output for the last dollar spent on the input, is estimated. Rational managers should keep investing in IT, until an additional unit of the input creates no more value than its costs, leading to a net marginal product of zero. Apart from some early studies, empirical evidence suggests that IT investment yields not 1720
1 3 Lost intranslation: IT business value research andresource… In a third step, we conducted a backwards search by screening the bibliographies of our identified studies. Working papers or conference papers were not considered due to their preliminary stage. Moreover, we did not consider any books or book chapters due to the difficulty of assessing their academic rigor. Overall, we obtained an additional 23 studies. In a fourth step, we performed a forward search. The Web of Science database was used to retrieve articles citing the studies collected so far, which led to the addition of another 29 articles. In a fifth step, we scanned the references of prior reviews and meta-analyses in the field of ITBV (Gerow etal. 2014; Mandrella etal. 2020; Sabherwal and Jeyaraj 2015; Schryen 2013; Wiengarten etal. 2013) to ensure that we did not miss any relevant articles. This resulted in the inclusion of three papers and a final sample of 227 studies. An overview of the identified studies is provided in Online Appendix A. The overview contains information for each study on the dataset used, the consideration of environmental factors, the adopted theory, the method applied to examine complementarities, and the non-IT resources that were examined. 5 The state ofresource complementarity inITBV research To organize research on complementary non-IT resources and gain deeper insights regarding their relationship with IT resources, we categorized the identified papers according to our classification of complementary non-IT resources (see Table 2). Because some papers examine multiple complementary non-IT resources, a study can be assigned to more than one category. We utilized the measure (e.g. the different survey items) of the complementary non-IT resource in each study to determine the appropriate category. Thereby, we were able to classify all studies in at least one of the suggested categories (see Online Appendix A), which further validates our proposed classification of complementary non-IT resources. 5.1 Strategy Strategy can be understood as the identification of a company’s long-term objective, adoption of courses of action, and allocation of resources required to accomplish these goals (Chandler 1962). We identified 104 studies that analyze the performance impact of IT in combination with strategy, making this by far the largest research field. Thereby, studies use a broad range of fit perspectives: matching (e.g. Gómez etal. 2016), moderation (e.g. Tallon and Pinsonneault 2011), profile deviation (e.g. Sabherwal etal. 2019), covariation (e.g. Chatzoglou etal. 2011), or gestalts (e.g. Pollalis 2003). While most studies are at the firm level, in recent years a shift towards more process-level studies has taken place (e.g. Tallon 2008, 2012; Tallon etal. 2016). Also, a variety of scales or proxies are applied to measure alignment between IT and business strategy such as Venkatraman’s (1989a) Strategic 1727
S.Schweikl, R.Obermaier 1 3 Orientation of Business Enterprises (STROBE) and/or Chan’s etal. (1997) Strategic Orientation of the Existing Portfolio of Information Systems (STROPIS) scale (e.g., Sabherwal and Chan 2001), Miles and Charles’s (1978) defenders, prospectors, and analyzers typology (e.g. Croteau and Bergeron 2001), Treacy and Wierseman’s (1995) value disciplines typology (e.g. Tallon 2008), Porter’s (1980) generic business strategies (e.g. Yin etal. 2020), or fit/integration between business and IT plan (e.g. Kearns and Lederer 2004). For all the different strategy measures, fit perspectives, and observation levels, the studies included in our sample consistently support that the alignment between IT and business strategy improves firm performance (see also Gerow etal. 2014). For instance, Chan etal. (1997) find a positive effect of strategic IT alignment on perceived IS effectiveness and perceived firm performance. Likewise, Wu et al. (2015) show a positive link between realized strategic IT alignment and organizational performance. At times, studies report mixed results with strategic IT alignment only impacting some performance aspects (e.g. Croteau and Bergeron 2001), affecting performance only when specific business strategies are pursued (e.g. Chan etal. 2006), only when certain fit perspectives are utilized (e.g. Cragg etal. 2002), or only at certain observation levels (e.g. Queiroz 2017). Seldom studies also offer contradictory results. For instance, Palmer and Markus (2000) demonstrate that retail firms with a matched IT and business strategy do not perform significantly better than those with an un-matched IT and business strategy. 5.2 Structure The structure of an organization can be defined as “the sum total of the ways in which it divides its labor into distinct tasks and then achieves coordination among them” (Mintzberg 1979, p. 2). We identified 44 studies that analyze the performance impact of IT in combination with structure. Organizational structure spans multiple sub-categories including formalization (emphasis on formal rules), specialization (number of distinct job titles), functional differentiation (number of departments), centralization (employee participation in decision making), professionalization (percentage of professional staff members), and vertical differentiation (number of hierarchical levels) (Damanpour 1991). While some studies investigate the alignment of IT resources with different sub-categories of structure (Bergeron etal. 2001, 2004; Buttermann etal. 2008; Chatzoglou etal. 2011; Raymond etal. 1995), the predominant research focus is on the relationship between IT and (de-)centralization. While IT enables enterprises to process and transfer ever-larger amounts of data, boundedly rational organizations are constrained in the amount of information they can effectively absorb (Tambe etal. 2012). As employees can only process a limited amount of information, too much input can lead to an information overload and negatively affect performance (Andersen 2005). In order to circumvent this phenomenon, firms must improve information flow within an organization (Bresnahan etal. 2002). This can be achieved by an increase in lateral communication and a stronger reliance on decentralized decision-making by flattening hierarchies and granting more decision power to individual workers (Bertschek and Kaiser 2004). 1728
1 3 Lost intranslation: IT business value research andresource… However, the empirical evidence regarding the complementarity between IT and a decentralization is ambiguous. While some studies indicate a synergistic relationship (Albadvi etal. 2007; Brynjolfsson etal. 2002; Francalanci and Galal 1998) or a negative interaction between centralization and IT (Fink and Sukenik 2011), others find no significant interaction effect between IT and decentralization (Andersen and Segars 2001; Arvanitis 2005; Arvanitis and Loukis 2009; Arvanitis etal. 2016; Bertschek and Kaiser 2004; Caroli and van Reenen 2001; Dostie and Jayaraman 2012; Moshiri and Simpson 2011; Rasel 2016) as well as mixed results (Commander etal. 2011; Mohamad etal. 2017), while yet others even indicate a suppressing relationship (Giuri etal. 2008). Thus, it appears that IT resources are not per se complementary to a decentralized decision structure. 5.3 Practice Practices are “policies, programs, or systems that encourage or allow certain behaviors” (Gibson etal. 2007, p. 1467). We identified 56 studies that analyze the performance impact of IT in combination with practices. Thereby, studies focus mostly either on human resource practices including promoting teamwork (e.g. Bresnahan etal. 2002), job rotation (e.g. Stucki and Wochner 2019), flexible working arrangements (e.g. Moshiri and Simpson 2011), hiring (e.g. Brynjolfsson et al. 2002), worker training (e.g. Prasad and Heales 2010), incentive systems (e.g. Aral et al. 2012), and worker monitoring (e.g. Commander etal. 2011) or externally focused practices such as benchmarking (e.g. Tambe et al. 2012), supplier management (e.g. Vickery etal. 2010), and customer involvement initiatives (e.g. Saldanha etal. 2017). The introduction of IT can lead to a shift in the role of employees and to a redeployment of workers who have to be flexible and take on new tasks. Given these alterations due to IT adoption, firms may have to implement new guidelines for hiring, promoting, firing, and training their workers. Bloom etal. (2012) conclude that US-lead companies in Europe deploy IT more productive than European ones due to a more pro-active human resources management, which is characterized by faster promotions of high-performers but also quicker layoffs of below-average employees. In addition, with the implementation of IT it becomes easier for firms to monitor the performance of employees. By combining data on workflows, financial transactions, etc. with human resource data, executives are able to align the tasks of employees with the overall business strategy, assessing the demand they put on employees as well as keeping track with their performance (Aral etal. 2012). Therefore, IT can support executives in monitoring and evaluating employee performance, which facilitates performance-based incentive systems and assists in directing employees’ efforts towards the objectives of the firm. For instance, Aral etal. (2012) indicate that the adoption of human capital management software is associated with a substantial productivity increase when it is implemented in combination with performance pay and human resource analytics practices. Besides, companies may also have to adopt new externally focused practices. As IT enables firms to have closer relations with external partners and process large 1729
S.Schweikl, R.Obermaier 1 3 external information streams, firms may need to implement practices that take advantage of these new possibilities. For example, Tambe etal. (2012) indicate that the combination of externally focused, decentralization, and IT enhances firm performance more than the sum of their separate effects. 5.4 Process Processes are a set of defined activities or tasks to achieve distinct business outcomes (Davenport and Short 1990). We identified 46 studies that analyze the performance impact of IT in combination with processes. The research scope ranges from studies that investigate firm-wide process reengineering (e.g. Albadvi etal. 2007) to studies that focus on specific types of organizational processes such as knowledge management processes (e.g. Tanriverdi 2005), production processes (e.g. Ward and Zhou 2006), relational processes (e.g. Reinartz etal. 2004), and supply chain processes (e.g. Liu etal. 2016). As IT facilitates the flow of information within and between firms and reduces the cost of coordinating business activities, it enables a transformation of business processes (Grover etal. 1998). Thus, with the adoption of IT, firms may need to reengineer processes or couple IT with existing processes to realize its business value. Thereby, some studies suggest that the alignment of IT and organizational processes directly improves firm performance. For example, Devaraj and Kohli (2000) indicate that joint adoption of business process re-engineering and IT investment leads to improved profitability for hospitals. Similarly, Ramirez etal. (2010) find that a significant improvement of firm productivity and market value from business process re-engineering only appears when it is implemented in combination with IT. Others propose that the synergistic relationship between IT and organizational processes affects firm performance indirectly via the emergence of IT-enabled organizational capabilities. For instance, Tanriverdi (2005) demonstrate that the interplay between IT infrastructure and different management processes enables knowledge management capabilities, which ultimately improve firm performance. Bendoly et al. (2012) show that information system (IS) capabilities enhance the effect of manufacturing-marketing process coordination and manufacturing-supply chain process coordination on market intelligence and supply-chain intelligence, which in turn increase new product development performance. 5.5 Culture Culture reflects the shared values, ideals, and convictions of organizational members, which manifest themselves in their behavior (Schein 1985). We identified 19 studies that analyze the performance impact of IT in combination with culture. Culture is an elusive concept that is hard to observe and requires the concurrent manipulation of complex human relationships and technologies, which makes it difficult to re-create and a powerful source of competitive advantage (Powell and Dent-Micallef 1997). For instance, an open communication culture is often seen 1730
1 3 Lost intranslation: IT business value research andresource… as complementary to IT as it facilitates knowledge exchange between employees and encourages closer cooperation of functional departments within an organization, resulting in more interdisciplinary and innovative solution approaches (Jeffers etal. 2008). Supporting this assertion, Ifinedo (2007) find that firms with an culture marked by information sharing and collaboration have higher ERP system success. However, Fawcett etal. (2011) show that investments in either supply chain connectivity or an information-sharing culture among supply chain members enhance operational performance and customer satisfaction, but there is no mutual reinforcement. Another aspect that has received research attention is an organizational culture that promotes the support and empowerment of employees (Gold etal. 2001; Kmieciak et al. 2012). Encouraging employees to interact, utilize their creativity, and increase their initiative to peruse innovative ideas, can create a sense of ownership and contribution among employees. Kmieciak etal. (2012) find that IT capability positively moderates the relation between employee empowerment and firm performance of small and medium enterprises, even suggesting that a corporate culture that promotes employee empowerment without the adoption of IT might negatively affect firm performance. Furthermore, a clear vision or commitment of an organization is needed to unify employees and develop an organizational purpose to direct resources and efforts towards a shared goal. For instance, Bradley etal. (2006) observe that the quality of the IT plan has a greater impact on IS success in enterprises that possess an entrepreneurial culture with a commitment to innovation than in those that exhibit a more formal and bureaucratic culture. 5.6 Top management support TMS reflects the “level of general support offered by top management […]” (Igbaria etal. 1997, p. 289). We found 22 studies that analyze the performance impact of IT in combination with TMS. Top management generally has an excellent oversight of the entire organization, which enables them to identify the areas where IT resources are required and can be adequately leveraged to add value to the business. Thus, managers should play a central role in planning the long-term orientation of the IT investment and be continuously involved in IT projects to ensure an effective and efficient utilization of IT resources. While some studies indicate that TMS enhances the impact of IT resources on organizational performance (e.g. Cohen 2008; Kearns and Sabherwal 2007), others suggest that a more nuanced perspective is needed. In particular, Weill (1992) shows that top management commitment increases the contribution of strategic IT investment to business performance. For transactional and informational IT investments, he finds, however, no significant moderation effect. Steelman etal. (2019), who divide IT into current IT investments and new IT investments, are able to show that organizational commitment to IT increases the marginal benefits of current IT investments for firms that pursue a defender strategy, but it decreases the marginal benefits, if they invest in new IT systems. They also find that the contrary is true for firms that pursue a prospector strategy. In sum, while TMS appears 1731
S.Schweikl, R.Obermaier 1 3 to be an important complement to IT resources, it seems that its importance varies depending on the relevance of the IT resource for a given business strategy. 5.7 Internal relations Internal relations describe individuals, groups, or departments collaborating across intra-organizational boundaries. We identified 30 studies that analyze the performance impact of IT in combination with internal relationships. Thereby, the alignment between IT and non-IT personal is often referred to as social alignment (Reich and Benbasat 2000) and has been analyzed at various aggregation levels, such as between individuals (e.g. Jeffers 2010), groups (e.g. Lee etal. 2008), or departments (e.g. Oh etal. 2014) as well as varying hierarchical levels like ties between line managers (e.g. Jeffers 2010) or Chief Information Officer (CIO) and Chief Executive Officer (CEO) (e.g. Li and Ye 1999). Close relations between IT and business functions are vital to enable mutual trust and encourage the sharing of resources to jointly create value (Wagner etal. 2014). When employees are more closely connected, they are more inclined to openly discuss problems and support another (Schlosser etal. 2015). By means of such an effective communication, employees share a common understanding of the role of IT within the organization, and IT professionals are able to identify and address the IT needs of an organization (et vice versa). Conversely, if there is mistrust between the IT and non-IT personal, informal contacts will be avoided, which may affect firm performance negatively as it hinders information sharing (Ray etal. 2005). Accordingly, Wagner etal. (2014) observe that mutual trust and respect between IT and business units has a positive effect on the business understanding of the IT unit, which enhances firm performance. Likewise, Schlosser etal. (2015) show that formal and informal integration mechanisms between business and IT improve social alignment, which in turn increases firm performance. Moreover, close links between business and IT managers are important, as the deployment of IT in value chain activities and its strategic role is impacted by the CIO’s involvement in top management team activities. For example, Li and Ye (1999) discover that IT investments have a more pronounced impact on financial performance, when there are closer ties between CEO and CIO. Karahanna and Preston (2013) show that trust between CIO and top management team leads to a closer alignment between IT and business strategy and, consequently, to an improved firm performance. 5.8 External relations External relations refer to a firm’s relationship with external partners and its reputation or brand (Ray etal. 2013). We identified 29 studies that analyze the performance impact of IT in combination with external relations. Close cooperation with external partners is inherently risky for a focal firm, as potentially sensitive information is shared, rendering a firm susceptible to 1732
1 3 Lost intranslation: IT business value research andresource… opportunistic and exploitative behavior (Miao et al. 2018). Accordingly, Powell and Dent-Micallef (1997, p. 382) state that “EDI systems combine intraand interorganizational information processing to facilitate sophisticated electronic interactions with suppliers. However, in the absence of open and trusting supplier relationships, such systems can do little but magnify existing suspicions […].” Thus, IT-based integration of external partners is only valuable, if there is a close enough involvement (Zhang and Yang 2016) and trust (Miao etal. 2018) between parties to share accurate and adequate information in a timely manner. For instance, Zhang et al. (2016) show that intra-organizational ICT in combination with information sharing and a cooperative relationship with buyers improves supplier performance. Besides, IT-based information exchange can help companies to combine their resources and capabilities to seize given business opportunities (Jiang and Zhao 2014). Therefore, the value created by the integration of IT for connecting interfirm processes depends largely on joint activities between organizations and common understanding how to leverage available resources. Rai etal. (2012) state that inter-firm IT capability enhance relational value co-creation when complemented by exchange of knowledge and ideas among senior (IT) executives. Furthermore, Liu etal. (2016) conclude that it is crucial for companies to align their IT competence with the scope of cooperation and resource sharing among its distribution partners. A neglected facet is the synergy of firm reputation or brand with IT. Every firm has some form of brand, which promises customers` specific benefits and raises certain expectations. Thereby, some brand orientations may be more synergistic with IT than others. Piccoli and Lui (2014) demonstrate that brand moderates the interaction between the effective use of an IT-enabled service channel and competitive performance in the hospitality sector. Specifically, one brand exhibits a direct positive impact of the IT-enabled service channel on the firm’s ability to exceed the revenue per available room of its rivals, whereas the other brand fails in doing so, even though both use the same standardized IT application. 5.9 Worker skill Worker skill reflects the qualifications and competence of employees that is not directly related or limited to technical abilities. We identified 15 studies that analyze the performance impact of IT in combination with worker skill. Thereby, measures for worker skill are mostly educational level (e.g. Giuri etal. 2008), but also the proportion of unskilled manual workers (e.g. Caroli and van Reenen 2001) or worker compensation (Saldanha etal. 2022). Rarely, a direct measure of worker skill (e.g. Aral and Weill 2007) or the fit between worker skill and job tasks (e.g. Ghasemaghaei etal. 2017) are employed. IT is considered superior to humans in performing most cognitive and manual routine tasks. For this reason, computers are used for routine operations such as putting pieces together at the assembly line or doing bookkeeping. In turn, the number of cognitive, non-routine tasks at the workplace increases, as computers have difficulties in identifying creative solutions to previously unknown problems, necessitating analytical and cognitive skills (Giuri etal. 2008). Thereby, particularly highly 1733
S.Schweikl, R.Obermaier 1 3 skilled workers seem to benefit from this shift in work tasks, as those have an easier time performing cognitive demanding tasks (Bresnahan etal. 2002). Yet, research on the complementarity between IT and worker skill is rather mixed. On the one hand, studies suggest a complementary relationship between IT and skilled labor (Bresnahan etal. 2002; Brynjolfsson etal. 2021; Giuri etal. 2008; Moshiri and Simpson 2011; Mouelhi 2009). On the other hand, studies find no significant positive interaction effects between IT and worker skill on organizational performance measures (Arvanitis etal. 2016; Bloom etal. 2012; Caroli and van Reenen 2001) or only in certain settings (Arvanitis 2005; Arvanitis and Loukis 2009). Thus, it appears that the presence of skilled workers does not necessarily enhance the value created by IT resources. 6 Discussion: shortcomings anddirections forfuture research The concept of resource complementary has been widely applied in ITBV research, yet it seems that so far research has primarily contemplated different pieces of the puzzle, although only by combining them it is possible to obtain a holistic picture and generate more profound insights. Accordingly, our review does not find evidence of a specific pair of IT and non-IT resources, whose relationship is always complementary, irrespective of the institutional or environmental context. Rather, it became apparent that research findings within a resource category diverged in several instances, at times even contradicting each other. For example, some studies identify a decentralized decision structure as a key complement to IT (e.g. Bresnahan etal. 2002; Brynjolfsson etal. 2002), while others find no significant effect (e.g. Arvanitis 2005; Bertschek and Kaiser 2004), and yet others even observe a negative association (Giuri etal. 2008). As an explanation for these ambiguous findings, we have identified five shortcomings in the current literature by systematically examining applied methodologies to detect complementarities, measurement of dependent and independent variables, consideration of environmental factors, and the underlying data sets. 6.1 Current shortcomings inITBV research andpotential resolutions 6.1.1 Shortcoming1: utilizing reductionist approaches We found that the vast majority of studies focuses on pairwise associations between IT and a single complementary non-IT resource (e.g. Chari etal. 2008; Jeffers etal. 2008). While the analysis of pairwise interactions is a valid approach, as it provides a high level of granularity (Drazin and van de Ven 1985), such a reductionist perspective has its drawbacks. The process of creating ITBV is multifaceted as demonstrated by the wide range of complementary non-IT resources that have been explored in empirical studies. Thus, one can argue that there is not necessarily a single non-IT resource critical 1734
1 3 Lost intranslation: IT business value research andresource… to the successful deployment of IT, but a full system of complementary non-IT resources needs to be in place. Therefore, the sole assessment of pairwise associations seems to be incomplete, as it lacks sufficient capacity to capture multivariate interaction between IT and several non-IT resources (Fink and Sukenik 2011). For instance, firm performance is affected differently when IT and organizational structure are mutually reinforcing, but there is a simultaneous lack of adequately skilled workers or a counteractive culture. In such cases, the analysis of two-way interactions leads to misleading insights, because it assumes that the whole system is decomposable into pairwise associations which can be examined independently, and the acquired knowledge can be re-aggregated to understand the system as a whole (Cao etal. 2011; Drazin and van de Ven 1985). By definition, however, complementarity means that the whole is more than the sum of its parts (Milgrom and Roberts 1990, 1995). Likewise, a system may fail, if only one single piece is missing, making any piecemeal view potentially deceptive (Nevo and Wade 2010; Someh etal. 2019). Therefore, the absence of complementary relationships between IT and a single non-IT resource cannot disregard the possibility of synergies, as the two resources may only become complementary when a third resource (or a set of resources) is added (Ennen and Richter 2010). Thus, complementarity effects may only emerge when a resource is embedded in an overall system that includes many elements. Yet, most of the empirical studies in our review follow a bivariate fit or a two-way interaction approach (see Online Appendix A). While some consider several complementary non-IT resources, they mostly analyze a multitude of separate pairwise interactions instead of taking a system approach (e.g. Albadvi etal. 2007). At least some studies extend this perspective by utilizing three-way-interactions between different resources to examine a larger set of complementarities (e.g. Tambe etal. 2012). Only a few studies apply a system approach by utilizing deviations from ideal profiles (e.g. Bergeron etal. 2001; Fink and Sukenik 2011; Liu etal. 2016), covariation analysis3 (e.g. Chen 2012; Gu and Jung 2013), cluster analysis (e.g. Bergeron etal. 2001, 2004; Buttermann etal. 2008; Pollalis 2003), or, more recently, fuzzyset qualitative comparative analysis (Park etal. 2017, 2020; Park and Mithas 2020). Nevertheless, even these studies still mostly encompass a small set of different heterogenous resources like IT, strategy, and structure (Bergeron etal. 2001, 2004) or IT, strategy, and processes (Pollalis 2003), limiting our knowledge on larger sets of synergistic resource configurations. In sum, we argue that research regarding complementary non-IT resources has to progress beyond a reductionist view, since there is still a major knowledge gap regarding different configurational recipes of IT and complementary non-IT resources that are necessary or sufficient to achieve a desired performance outcome. To address this issue, studies can apply currently underutilized approaches such as ideal profile deviation, cluster analysis, or fuzzy-set qualitative comparative analysis. 3 Fit as covariation is equivalent to utilizing reflective second-order factor modeling (see Polites etal. 2012). 1735
S.Schweikl, R.Obermaier 1 3 6.1.2 Shortcoming 2: employing monolithic IT resource measures A variety of studies tries to identify complementarities between IT and non-IT resources by utilizing monolithic IT measures (e.g., Bertschek and Kaiser 2004; Bresnahan et al. 2002). However, such an approach may result in an incomplete understanding and interpretation of the complementary nature of IT. Firms are pursuing diverging strategies, resulting in different IT investments and varying IT resources between firms (Aral and Weill 2007; Tallon etal. 2000). Under this assertion, utilizing a single, composite IT measure implies that the different types of IT such as ERP systems, data networks, electronic messaging systems, or computer-aided design (CAD) systems can be seen as a homogenous resource bundle. Given their different functions, areas of application, and strategic purposes this seems, however, rather doubtful. In that sense, a failure to disentangle IT is tantamount to assuming that either all firms have an equal bundle of IT resources or that there is no difference between the varying types of IT a firm possesses with respect to their interactions with complementary non-IT resources. Unfortunately, both of these assumptions are clearly flawed. Accordingly, empirical research has shown that investment in different types of IT may even require competing non-IT resource complements (Steelman etal. 2019; Stucki and Wochner 2019). Bloom etal. (2014) show that communication enhancing IT (e.g. intranets, e-mail) tend to reduce communication costs, which foster a centralized structure, as decisions will be passed up to the managers of the firm. In contrast, advanced IT (e.g. ERP systems, CAD systems) provide workers with the ability to solve a wide range of tasks on their own and lowers the information acquisition costs, facilitating a decentralized structure. Building on these insights, Stucki and Wochner (2019) indicate that greater employee voice promotes firm productivity when combined with advanced IT, but suppresses firm productivity when combined with intranets (et vice versa). Consequently, we propose that studies need to take a more nuanced perspective on IT resources and make a distinction between different types of IT when examining its complementarity with non-IT resources. Thereby, promising avenues to disentangle IT seem to be either along functional dimensions (Stucki and Wochner 2019) or its strategic purpose (Aral and Weill 2007) to generate more detailed insights. Of course, this also applies to the measure of the non-IT resource, as it is essential to conceptualize each resource onto the same level of analysis before assessing resource complementarity. 6.1.3 Shortcoming 3: neglecting environmental uncertainty We have already argued that the diverse subsystems of an organization should fit together to create business value from IT. There should, however, not only be a coherence between them, but also compatibility with environmental factors (Melville etal. 2004). These factors can be seen as a reflection of the uncertainty in the operating environment of an organization (Wade and Hulland 2004). Thereby, three distinct dimensions commonly characterize environmental uncertainty: heterogeneity, dynamism, and hostility (Miller and Friesen 1983). Heterogeneity refers to the 1736
1 3 Lost intranslation: IT business value research andresource… Andersen TJ (2005) The performance effect of computer-mediated communication and decentralized strategic decision making. J Bus Res 58:1059–1067 Andersen TJ, Segars AH (2001) The impact of IT on decision structure and firm performance: evidence from the textile and apparel industry. Inf Manag 39:85–100 Andrews D, Criscuolo C, Gal PN (2016) The best versus the rest: the global productivity slowdown, divergence across firms and the role of public policy. OECD working papers Aral S, Weill P (2007) IT assets, organizational capabilities, and firm performance: how resource allocations and organizational differences explain performance variation. Organ Sci 18:763–780 Aral S, Brynjolfsson E, Wu L (2012) Three-way complementarities: performance pay, human resource analytics, and information technology. Manag Sci 58:913–931 Arvanitis S (2005) Computerization, workplace organization, skilled labour and firm productivity: evidence for the Swiss business sector. Econ Innov New Technol 14:225–249 Arvanitis S, Loukis EN (2009) Information and communication technologies, human capital, workplace organization and labour productivity: a comparative study based on firm-level data for Greece and Switzerland. Inf Econ Policy 21:43–61 Arvanitis S, Loukis EN, Diamantopoulou V (2016) Are ICT, workplace organization, and human capital relevant for innovation? A comparative Swiss/Greek study. Int J Econ Bus 23:319–349 Barney J (1991) Firm resources and sustained competitive advantage. J Manag 17:99–120 Bartel A, Ichniowski C, Shaw K (2007) How does information technology affect productivity? Plantlevel comparisons of product innovation, process improvement, and worker skills. Q J Econ 122:1721–1758 Bendoly E, Bharadwaj A, Bharadwaj S (2012) Complementary drivers of new product development performance: cross-functional coordination, information system capability, and intelligence quality. Prod Oper Manag 21:653–667 Benitez-Amado J, Walczuch RM (2012) Information technology, the organizational capability of proactive corporate environmental strategy and firm performance: a resource-based analysis. Eur J Inf Syst 21:664–679 Bergeron F, Raymond L, Rivard S (2001) Fit in strategic information technology management research: an empirical comparison of perspectives. Omega 29:125–142 Bergeron F, Raymond L, Rivard S (2004) Ideal patterns of strategic alignment and business performance. Inf Manag 41:1003–1020 Bertschek I, Kaiser U (2004) Productivity effects of organizational change: microeconometric evidence. Manag Sci 50:394–404 Bharadwaj AS (2000) A resource-based perspective on information technology capability and firm performance: an empirical investigation. MIS Q 24:169–196 Black JA, Boal KB (1994) Strategic resources: traits, configurations and paths to sustainable competitive advantage. Strateg Manag J 15:131–148 Black SE, Lynch LM (2001) How to compete: the impact of workplace practices and information technology on productivity. Rev Econ Stat 83:434–445 Bloom N, Sadun R, van Reenen J (2012) Americans do IT better: US multinationals and the productivity miracle. Am Econ Rev 102:167–201 Bloom N, Garicano L, Sadun R, van Reenen J (2014) The distinct effects of information technology and communication technology on firm organization. Manag Sci 60:2859–2885 Bradley RV, Pridmore JL, Byrd TA (2006) Information systems success in the context of different corporate cultural types: an empirical investigation. J Manag Inf Syst 23:267–294 Bresnahan TF, Brynjolfsson E, Hitt LM (2002) Information technology, workplace organization, and the demand for skilled labor: firm-level evidence. Q J Econ 117:339–376 Brush TH, Artz KW (1999) Toward a contingent resource-based theory: the impact of information asymmetry on the value of capabilities in veterinary medicine. Strateg Manag J 20:223–250 Brynjolfsson E, Hitt LM (1998) Beyond the productivity paradox. Commun ACM 41:49–55 Brynjolfsson E, Hitt LM (2000) Beyond computation: information technology, organizational transformation and business performance. J Econ Perspect 14:23–48 Brynjolfsson E, Milgrom P (2013) Complementarity in organizations. In: Gibbons R, Roberts J (eds) The Handbook of organizational economics, vol 11. Princeton University Press, Princeton, pp 11–55 Brynjolfsson E, Hitt LM, Yang S (2002) Intangible assets: computers and organizational capital. Brook Pap Econ Act 1:137–181 Brynjolfsson E, Jin W, McElheran K (2021) The power of prediction: predictive analytics, workplace complements, and business performance. Bus Econ 56:217–239 1743
S.Schweikl, R.Obermaier 1 3 Burns T, Stalker GM (1961) The management of innovation. Tavistock, London Buttermann G, Germain R, Iyer KNS (2008) Contingency theory “fit” as gestalt: an application to supply chain management. Transp Res E Logist Transp Rev 44:955–969 Cao G, Wiengarten F, Humphreys P (2011) Towards a contingency resource-based view of IT business value. Syst Pract Action Res 24:85–106 Cao G, Duan Y, Cadden T, Minocha S (2016) Systemic capabilities: the source of IT business value. Inf Technol People 29:556–579 Caroli E, van Reenen J (2001) Skill-biased organizational change? Evidence from a panel of British and French establishments. Q J Econ 116:1449–1492 Chae H-C, Koh CE, Prybutok VR (2014) Information technology capability and firm performance: contradictory findings and their possible causes. MIS Q 38:305–326 Chan YE, Huff SL, Barclay DW, Copeland DG (1997) Business strategic orientation, information systems strategic orientation, and strategic alignment. Inf Syst Res 8:125–150 Chan YE, Sabherwal R, Thatcher JB (2006) Antecedents and outcomes of strategic IS alignment: an empirical investigation. IEEE Trans Eng Manag 53:27–47 Chandler AD (1962) Strategy and structures: chapters in the history of the industrial enterprise. MIT Press, Cambridge Chari M, Devaraj S, David P (2008) Research note—the impact of information technology investments and diversification strategies on firm performance. Manag Sci 54:224–234 Chatterjee S, Wernerfelt B (1991) The link between resources and type of diversification: theory and evidence. Strateg Manag J 12:33–48 Chatzoglou PD, Diamantidis AD, Vraimaki E, Vranakis SK, Kourtidis DA (2011) Aligning IT, strategic orientation and organizational structure. Bus Process Manag J 17:663–687 Chen J-L (2012) The synergistic effects of IT-enabled resources on organizational capabilities and firm performance. Inf Manag 49:142–150 Choe J-m (2003) The effect of environmental uncertainty and strategic applications of IS on a firm’s performance. Inf Manag 40:257–268 Clemons EK, Row MC (1991) Sustaining IT advantage: the role of structural differences. MIS Q 15:275–292 Cohen JF (2008) Contextual determinants and performance implications of information systems strategy planning within South African firms. Inf Manag 45:547–555 Commander S, Harrison R, Menezes-Filho N (2011) ICT and productivity in developing countries: new firm-level evidence from Brazil and India. Rev Econ Stat 93:528–541 Cragg P, King M, Hussin H (2002) IT alignment and firm performance in small manufacturing firms. J Strateg Inf Syst 11:109–132 Croteau A-M, Bergeron F (2001) An information technology trilogy: business strategy, technological deployment and organizational performance. J Strateg Inf Syst 10:77–99 Damanpour F (1991) Organizational innovation: a meta-analysis of effects of determinants and moderators. Acad Manag J 34:555–590 Davenport TH, Short JE (1990) The new industrial engineering: information technology and business process redesign. MIT Sloan Manag Rev 31:11–27 Davern MJ, Kauffman RJ (2000) Discovering potential and realizing value from information technology investments. J Manag Inf Syst 16:121–143 Dedrick J, Gurbaxani V, Kraemer KL (2003) Information technology and economic performance: a critical review of the empirical evidence. ACM Comput Surv 35:1–28 Devaraj S, Kohli R (2000) Information technology payoff in the health-care industry: a longitudinal study. J Manag Inf Syst 16:41–67 Doherty NF, Ashurst C, Peppard J (2012) Factors affecting the successful realisation of benefits from systems development projects: findings from three case studies. J Inf Technol 27:1–16 Donaldson L (2001) The contingency theory of organizations. Sage, Thousand Oaks Dostie B, Jayaraman R (2012) Organizational redesign, information technologies and workplace productivity. BE J Econ Anal Policy 12:1–39 Drazin R, van de Ven (1985) Alternative forms of fit in contingency theory. Adm Sci Q 30:514–539 Ennen E, Richter A (2010) The whole is more than the sum of its parts—or is it? A review of the empirical literature on complementarities in organizations. J Manag 36:207–233 Fawcett SE, Wallin C, Allred C, Fawcett AM, Magnan GM (2011) Information technology as an enabler of supply chain collaboration: a dynamic-capabilities perspective. J Supply Chain Manag 47:38–59 1744
1 3 Lost intranslation: IT business value research andresource… Fink L, Sukenik E (2011) The effect of organizational factors on the business value of IT: universalistic, contingency, and configurational predictions. Inf Syst Manag 28:304–320 Fisch C, Block J (2018) Six tips for your (systematic) literature review in business and management research. Manag Rev Q 68:103–106 Forés B (2019) Beyond gathering the ‘low-hanging fruit’ of green technology for improved environmental performance: an empirical examination of the moderating effects of proactive environmental management and business strategies. Sustainability 11:1–34 Francalanci C, Galal H (1998) Information technology and worker composition: determinants of productivity in the life insurance industry. MIS Q 22:227–241 Gal P, Nicoletti G, von Rüden C, Sorbe S, Renault T (2019) Digitalization and productivity: in search of the holy grail—firm-level empirical evidence from European countries. Int Prod Monit 37:39–71 Gerow JE, Grover V, Thatcher JB, Roth PL (2014) Looking toward the future of IT-business strategic alignment through the past: a meta-analysis. MIS Q 38:1059–1085 Gerow JE, Thatcher JB, Grover V (2015) Six types of IT-business strategic alignment: an investigation of the constructs and their measurement. Eur J Inf Syst 24:465–491 Ghasemaghaei M, Hassanein K, Turel O (2017) Increasing firm agility through the use of data analytics: the role of fit. Decis Support Syst 101:95–105 Gibson CB, Porath CL, Benson GS, Lawler EE III (2007) What results when firms implement practices: the differential relationship between specific practices, firm financial performance, customer service, and quality. J Appl Psychol 92:1467–1480 Giuri P, Torrisi S, Zinovyeva N (2008) ICT, skills, and organizational change: evidence from Italian manufacturing firms. Ind Corp Chang 17:29–64 Gold AH, Malhotra A, Segars AH (2001) Knowledge management: an organizational capabilities perspective. J Manag Inf Syst 18:185–214 Gómez J, Salazar I, Vargas P (2016) Firm boundaries, information processing capacity, and performance in manufacturing firms. J Manag Inf Syst 33:809–842 Grant RM (1991) The resource-based theory of competitive advantage: implications for strategy formulation. Calif Manag Rev 33:114–135 Grant RM (1996) Prospering in dynamically-competitive environments: organizational capability as knowledge integration. Organ Sci 7:375–387 Grover V, Kohli R (2012) Cocreating IT value: new capabilities and metrics for multifirm environments. MIS Q 36:225–232 Grover V, Teng J, Segars AH, Fiedler K (1998) The influence of information technology diffusion and business process change on perceived productivity: the IS executive’s perspective. Inf Manag 34:141–159 Gu JW, Jung HW (2013) The effects of IS resources, capabilities, and qualities on organizational performance: an integrated approach. Inf Manag 50:87–97 Hammer M (1990) Reengineering work: don’t automate, obliterate. Harv Bus Rev 68:104–112 Henderson JC, Venkatraman N (1993) Strategic alignment: leveraging information technology for transforming organizations. IBM Syst J 32:4–16 Hooper VA, Huff SL, Thirkell PC (2010) The impact of IS-marketing alignment on marketing performance and business performance. Data Base Adv Inf Syst 41:36–55 Ifinedo P (2007) Interactions between organizational size, culture, and structure and some IT factors in the context of ERP success assessment: an exploratory investigation. J Comput Inf Syst 47:28–44 Igbaria M, Zinatelli N, Cragg P, Cavaye ALM (1997) Personal computing acceptance factors in small firms: a structural equation model. MIS Q 21:279–305 Jeffers PI (2010) Embracing sustainability. Int J Oper Prod Manag 30:260–287 Jeffers PI, Muhanna WA, Nault BR (2008) Information technology and process performance: an empirical investigation of the interaction between IT and non-IT resources. Decis Sci 39:703–735 Jiang Y, Zhao J (2014) Co-creating business value of information technology. Ind Manag Data Syst 114:53–69 Kappelman L, Maurer C, McLean ER, Kim K, Johnson VL, Snyder M, Torres R (2021) The 2020 SIM IT issues and trends study. MIS Q Executive 20:69–107 Karahanna E, Preston DS (2013) The effect of social capital of the relationship between the CIO and top management team on firm performance. J Manag Inf Syst 30:15–56 Kawakami T, Barczak G, Durmuşoğlu SS (2015) Information technology tools in new product development: the impact of complementary resources. J Prod Innov Manag 32:622–635 1745
S.Schweikl, R.Obermaier 1 3 Kearns GS, Lederer AL (2004) The impact of industry contextual factors on IT focus and the use of IT for competitive advantage. Inf Manag 41:899–919 Kearns GS, Sabherwal R (2007) Antecedents and consequences of information systems planning integration. IEEE Trans Eng Manag 54:628–643 Kim G, Shin B, Kim KK, Lee HG (2011) IT capabilities, process-oriented dynamic capabilities, and firm financial performance. J Assoc Inf Syst 12:487–517 Kmieciak R, Michna A, Meczynska A (2012) Innovativeness, empowerment and IT capability: evidence from SMEs. Ind Manag Data Syst 112:707–717 Kohli R, Grover V (2008) Business value of IT: an essay on expanding research directions to keep up with the times. J Assoc Inf Syst 9:23–39 Lavie D (2006) The competitive advantage of interconnected firms: an extension of the resource-based view. Acad Manag Rev 31:638–658 Lee SM, Kim K, Paulson P, Park H (2008) Developing a socio-technical framework for business-IT alignment. Ind Manag Data Syst 108:1167–1181 Leidner DE, Kayworth T (2006) A review of culture in information systems research: toward a theory of information technology culture conflict. MIS Q 30:357–399 Li M, Ye LR (1999) Information technology and firm performance: linking with environmental, strategic and managerial contexts. Inf Manag 35:43–51 Liu H, Wei S, Ke W, Wei KK, Hua Z (2016) The configuration between supply chain integration and information technology competency: a resource orchestration perspective. J Oper Manag 44:13–29 Mandrella M, Trang S, Kolbe LM (2020) Synthesizing and integrating research on IT-based value cocreation: a meta-analysis. J Assoc Inf Syst 21:388–427 Masli A, Richardson VJ, Sanchez JM, Smith RE (2011) The business value of IT: a synthesis and framework of archival research. J Inf Syst 25:81–116 Mata FJ, Fuerst WL, Barney JB (1995) Information technology and sustained competitive advantage: a resource-based analysis. MIS Q 19:487–505 Melville N, Kraemer K, Gurbaxani V (2004) Information technology and organizational performance: an integrative model of IT business value. MIS Q 28:283–322 Miao F, Wang G, Jiraporn P (2018) Key supplier involvement in IT-enabled operations: when does it lead to improved performance? Ind Mark Manag 75:134–145 Miles RE, Charles CS (1978) Organizational strategy, structure, and process. Acad Manag Rev 3:546–562 Milgrom P, Roberts J (1990) The economics of modern manufacturing: technology, strategy, and organization. Am Econ Rev 80:511–528 Milgrom P, Roberts J (1994) Complementarities and systems: understanding Japanese economic organization. Est Econ 9:3–42 Milgrom P, Roberts J (1995) Complementarities and fit strategy, structure, and organizational change in manufacturing. J Acc Econ 19:179–208 Miller D, Friesen PH (1983) Strategy-making and environment: the third link. Strateg Manag J 4:221–235 Mintzberg H (1979) The structuring of organizations. Prentice-Hall, Englewood Cliffs Mohamad A, Zainuddin Y, Alam N, Kendall G (2017) Does decentralized decision making increase company performance through its information technology infrastructure investment? Int J Acc Inf Syst 27:1–15 Moshiri S, Simpson W (2011) Information technology and the changing workplace in Canada: firm-level evidence. Ind Corp Chang 20:1601–1636 Mouelhi RBA (2009) Impact of the adoption of information and communication technologies on firm efficiency in the Tunisian manufacturing sector. Econ Model 26:961–967 Musiolik J, Markard J, Hekkert M (2012) Networks and network resources in technological innovation systems: towards a conceptual framework for system building. Technol Forecast Soc Change 79:1032–1048 Nadkarni S, Prügl R (2021) Digital transformation: a review, synthesis and opportunities for future research. Manag Rev Q 71:233–341 Nevo S, Wade MR (2010) The formation and value of IT-enabled resources: antecedents and consequences of synergistic relationships. MIS Q 34:163–183 Nadler DA, Tushman ML (1980) A model for diagnosing organizational behavior. Organ Dyn 9:35–51 Oh W, Pinsonneault A (2007) On the assessment of the strategic value of information technologies: conceptual and analytical approaches. MIS Q 31:239–265 Oh S, Yang H, Kim SW (2014) Managerial capabilities of information technology and firm performance: role of e-procurement system type. Int J Prod Res 52:4488–4506 1746
1 3 Lost intranslation: IT business value research andresource… Palmer JW, Markus ML (2000) The performance impacts of quick response and strategic alignment in specialty retailing. Inf Syst Res 11:241–259 Palvia P, ChauPatrick YK, Kakhki MD, Ghoshal T, Uppala V, Wang W (2017) A decade plus long introspection of research published in Information & Management. Inf Manag 54:218–227 Park Y, Mithas S (2020) Organized complexity of digital business strategy: a configurational perspective. MIS Q 44:85–128 Park Y, El Sawy OA, Fiss P (2017) The role of business intelligence and communication technologies in organizational agility: a configurational approach. J Assoc Inf Syst 18:648–686 Park Y, Pavlou PA, Saraf N (2020) Configurations for achieving organizational ambidexterity with digitization. Inf Syst Res 31:1376–1397 Penrose E (1959) The theory of the growth of the firm. Wiley, New York Piccoli G, Ives B (2005) IT-dependent strategic initiatives and sustained competitive advantage: a review and synthesis of the literature. MIS Q 29:747–776 Piccoli G, Lui T-W (2014) The competitive impact of information technology: can commodity IT contribute to competitive performance? Eur J Inf Syst 23:616–628 Polites GL, Roberts N, Thatcher J (2012) Conceptualizing models using multidimensional constructs: a review and guidelines for their use. Eur J Inf Syst 21:22–48 Pollalis YA (2003) Patterns of co-alignment in information-intensive organizations: business performance through integration strategies. Int J Inf Manag 23:469–492 Porter ME (1980) Competitive strategy. Free Press, New York Powell TC, Dent-Micallef A (1997) Information technology as competitive advantage: the role of human, business, and technology resources. Strateg Manag J 18:375–405 Prasad A, Heales J (2010) On IT and business value in developing countries: a complementarities-based approach. Int J Acc Inf Syst 11:314–335 Qrunfleh S, Tarafdar M (2014) Supply chain information systems strategy: impacts on supply chain performance and firm performance. Int J Prod Econ 147:340–350 Queiroz M (2017) Mixed results in strategic IT alignment research: a synthesis and empirical study. Eur J Inf Syst 26:21–36 Queiroz M, Tallon PP, Coltman T, Sharma R, Reynolds P (2020) Aligning the IT portfolio with business strategy: evidence for complementarity of corporate and business unit alignment. J Strateg Inf Syst 29:101623 Rai A, Pavlou PA, Im G, Du S (2012) Interfirm IT capability profiles and communications for cocreating relational value: evidence from the logistics industry. MIS Q 36:233–262 Ramirez R, Melville N, Lawler E (2010) Information technology infrastructure, organizational process redesign, and business value: an empirical analysis. Decis Support Syst 49:417–429 Rasel F (2016) Combining information technology and decentralized workplace organization: SMEs versus larger firms. Int J Econ Bus 23:199–241 Ray G, Muhanna WA, Barney JB (2005) Information technology and the performance of the customer service process: a resource-based analysis. MIS Q 29:625–652 Ray G, Xue L, Barney JB (2013) Impact of information technology capital on firm scope and performance: the role of asset characteristics. Acad Manag J 56:1125–1147 Raymond L, Paré G, Bergeron F (1995) Matching information technology and organizational structure: an empirical study with implications for performance. Eur J Inf Syst 4:3–16 Reich BH, Benbasat I (2000) Factors that influence the social dimension of alignment between business and information technology objectives. MIS Q 24:81–113 Reinartz W, Krafft M, Hoyer WD (2004) The customer relationship management process: its measurement and impact on performance. J Mark Res 41:293–305 Rowe F (2014) What literature review is not: diversity, boundaries and recommendations. Eur J Inf Syst 23:241–255 Ryoo SY, Koo C (2013) Green practices-IS alignment and environmental performance: the mediating effects of coordination. Inf Syst Front 15:799–814 Sabherwal R, Chan YE (2001) Alignment between business and IS strategies: a study of prospectors, analyzers, and defenders. Inf Syst Res 12:11–33 Sabherwal R, Jeyaraj A (2015) Information technology impacts on firm performance: an extension of Kohli and Devaraj (2003). MIS Q 39:809–836 Sabherwal R, Sabherwal S, Havakhor T, Steelman Z (2019) How does strategic alignment affect firm performance? The roles of information technology investment and environmental uncertainty. MIS Q 43:453–474 1747
S.Schweikl, R.Obermaier 1 3 Saldanha T, Mithas S, Krishnan MS (2017) Leveraging customer involvement for fueling innovation: the role of relational and analytical information processing capabilities. MIS Q 41:267–286 Saldanha T, Kathuria A, Khuntia J, Konsynski BR (2022) Ghosts in the machine: how marketing and human capital investments enhance customer growth when innovative services leverage self-service technologies. Inf Syst Res 33:76–109 Sanders NR (2005) IT alignment in supply chain relationships: a study of supplier benefits. J Supply Chain Manag 41:4–13 Saunders A, Brynjolfsson E (2016) Valuing information technology related intangible assets. MIS Q 40:83–110 Schein EH (1985) Organizational culture and leadership. Jossey-Bass, San Francisco Schlosser F, Beimborn D, Weitzel T, Wagner H-T (2015) Achieving social alignment between business and IT—an empirical evaluation of the efficacy of IT governance mechanisms. J Inf Technol 30:119–135 Schryen G (2013) Revisiting IS business value research: what we already know, what we still need to know, and how we can get there. Eur J Inf Syst 22:139–169 Schwarz A, Kalika M, Kefi H, Schwarz C (2010) A dynamic capabilities approach to understanding the impact of IT-enabled businesses processes and IT-business alignment on the strategic and operational performance of the firm. Commun AIS 26:57–84 Schweikl S, Obermaier R (2020) Lessons from three decades of IT productivity research: towards a better understanding of IT-induced productivity effects. Manag Rev Q 70:461–507 Scott Morton M (1991) Corporation of the 1990s: information technology and organizational transformation. Oxford University Press, New York Scott J (1999) The FoxMeyer Drugs’ bankruptcy: was it a failure of ERP? In: AMCIS 1999 proceedings, 80 Shin N (2001) The impact of information technology on financial performance: the importance of strategic choice. Eur J Inf Syst 10:227–236 Solow RM (1987) We’d better watch out. New York Times, New York Someh I, Shanks G, Davern M (2019) Reconceptualizing synergy to explain the value of business analytics systems. J Inf Technol 34:371–391 Steelman ZR, Havakhor T, Sabherwal R, Sabherwal S (2019) Performance consequences of information technology investments: implications of emphasizing new or current information technologies. Inf Syst Res 30:204–218 Stucki T, Wochner D (2019) Technological and organizational capital: where complementarities exist. J Econ Manag Strategy 28:458–487 Tallon PP (2008) A process-oriented perspective on the alignment of information technology and business strategy. J Manag Inf Syst 24:227–268 Tallon PP (2012) Value chain linkages and the spillover effects of strategic information technology alignment: a process-level view. J Manag Inf Syst 28:9–44 Tallon PP, Pinsonneault A (2011) Competing perspectives on the link between strategic information technology alignment and organizational agility: insights from a mediation model. MIS Q 35:463–486 Tallon PP, Kraemer KL, Gurbaxani V (2000) Executives’ perceptions of the business value of information technology: a process-oriented approach. J Manag Inf Syst 16:145–173 Tallon P, Queiroz M, Coltman TR, Sharma R (2016) Business process and information technology alignment: construct conceptualization, empirical illustration, and directions for future research. J Assoc Inf Syst 17:563–589 Tambe P, Hitt LM, Brynjolfsson E (2012) The extroverted firm: how external information practices affect innovation and productivity. Manag Sci 58:843–859 Tanriverdi H (2005) Information technology relatedness, knowledge management capability, and performance of multibusiness firms. MIS Q 29:311–334 Teece DJ, Pisano G, Shuen A (1997) Dynamic capabilities and strategic management. Strateg Manag J 18:509–533 Trainor KJ, Andzulis JM, Rapp A, Agnihotri R (2014) Social media technology usage and customer relationship performance: a capabilities-based examination of social CRM. J Bus Res 67:1201–1208 Tranfield D, Denyer D, Smart P (2003) Towards a methodology for developing evidence-informed management knowledge by means of systematic review. Br J Manag 14:207–222 Treacy M, Wierseman F (1995) The discipline of market leaders. Addison Wesley, Reading Umanath NS (2003) The concept of contingency beyond “It depends”: illustrations from IS research stream. Inf Manag 40:551–562 1748
1 3 Lost intranslation: IT business value research andresource… Venkatraman N (1989a) Strategic orientation of business enterprises: the construct, dimensionality, and measurement. Manag Sci 35:942–962 Venkatraman N (1989b) The concept of fit in strategy research: toward verbal and statistical correspondence. Acad Manag Rev 14:423–444 Vickery SK, Droge C, Setia P, Sambamurthy V (2010) Supply chain information technologies and organisational initiatives: complementary versus independent effects on agility and firm performance. Int J Prod Res 48:7025–7042 Wade M, Hulland J (2004) The resource-based view and information systems research: review, extension, and suggestions for future research. MIS Q 28:107–142 Wagner H-T, Beimborn D, Weitzel T (2014) How social capital among information technology and business units drives operational alignment and IT business value. J Manag Inf Syst 31:241–272 Ward P, Zhou H (2006) Impact of information technology integration and lean/just-in-time practices on lead-time performance. Decis Sci 37:177–203 Webster J, Watson RT (2002) Analyzing the past to prepare for the future: writing a literature review. MIS Q 26:13–23 Wei S, Yin J, Chen W (2022) How big data analytics use improves supply chain performance: considering the role of supply chain and information system strategies. Int J Logist Manag 33:620–643 Weill P (1992) The relationship between investment in information technology and firm performance: a study of the valve manufacturing sector. Inf Syst Res 3:307–333 Weill P, Olson MH (1989) An assessment of the contingency theory of management information systems. J Manag Inf Syst 6:59–86 Wernerfelt B (1984) A resource-based view of the firm. Strateg Manag J 5:171–180 Wiengarten F, Humphreys P, Cao G, McHugh M (2013) Exploring the important role of organizational factors in IT business value: taking a contingency perspective on the resource-based view. Int J Manag Rev 15:30–46 Wu SP-J, Straub DW, Liang T-P (2015) How information technology governance mechanisms and strategic alignment influence organizational performance: insights from a matched survey of business and IT managers. MIS Q 39:497–518 Yang Z, Sun J, Zhang Y, Wang Y (2017) Green, green, it’s green: a triad model of technology, culture, and innovation for corporate sustainability. Sustainability 9:1–23 Yang Z, Sun J, Zhang Y, Wang Y (2018) Peas and carrots just because they are green? Operational fit between green supply chain management and green information system. Inf Syst Front 20:627–645 Yayla AA, Hu Q (2012) The impact of IT-business strategic alignment on firm performance in a developing country setting: exploring moderating roles of environmental uncertainty and strategic orientation. Eur J Inf Syst 21:373–387 Yin J, Wei S, Chen X, Wei J (2020) Does it pay to align a firm’s competitive strategy with its industry IT strategic role? Inf Manag 57:103391 Zander I, Zander U (2005) The inside track: on the important (but neglected) role of customers in the resource-based view of strategy and firm growth. J Manag Stud 42:1519–1548 Zhang H, Yang F (2016) The impact of external involvement on new product market performance. Ind Manag Data Syst 116:1520–1539 Zhang X, van Donk DP, van der Vaart T (2016) The different impact of inter-organizational and intraorganizational ICT on supply chain performance. Int J Oper Prod Manag 36:803–824 Zhu K (2004) The complementarity of information technology infrastructure and e-commerce capability: a resource-based assessment of their business value. J Manag Inf Syst 21:167–202 Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. 1749