Exploring the online presence of food SMEs: a study on configurations and determinants in the north-east of Italy

Checchinato, Francesca; Finotto, Vladi; Mauracher, Christine Article Exploring the online presence of food SMEs: a study on configurations and determinants in the north-east of Italy Cogent Business & Management Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Checchinato, Francesca; Finotto, Vladi; Mauracher, Christine (2024) : Exploring the online presence of food SMEs: a study on configurations and determinants in the north-east of Italy, Cogent Business & Management, ISSN 2331-1975, Taylor & Francis, Abingdon, Vol. 11, Iss. 1, pp. 1-16, https://doi.org/10.1080/23311975.2024.2398190 This Version is available at: https://hdl.handle.net/10419/326541 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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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/ Cogent Business & Management ISSN: 2331-1975 (Online) Journal homepage: www.tandfonline.com/journals/oabm20 Exploring the online presence of food SMEs: a study on configurations and determinants in the north-east of Italy Francesca Checchinato, Vladi Finotto & Christine Mauracher To cite this article: Francesca Checchinato, Vladi Finotto & Christine Mauracher (2024) Exploring the online presence of food SMEs: a study on configurations and determinants in the north-east of Italy, Cogent Business & Management, 11:1, 2398190, DOI: 10.1080/23311975.2024.2398190 To link to this article: https://doi.org/10.1080/23311975.2024.2398190 © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group Published online: 04 Sep 2024. Submit your article to this journal Article views: 999 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=oabm20 Marketing | research article Cogent Business & ManageMent 2024, VoL. 11, no. 1, 2398190 Exploring the online presence of food SMEs: a study on configurations and determinants in the north-east of Italy Francesca checchinato , Vladi Finotto and christine Mauracher Department of Management, agrifood Management and innovation Lab, Ca’ Foscari university of Venice, Venice, italy ABSTRACT this study investigates sMes’ online presence and sheds light on the different digital marketing approaches of firms in the food sector. an original analytic framework is developed to perform a fine-grained analysis of the various configurations of online presence in a sample of 520 sMes in the north-east of italy. a cluster analysis of the empirical data related to firms’ online presence allowed the recognition of three configurations: pragmatists, laggards, and unfocused. the cluster analysis allows us to propose that the development of an online presence is far from being a unidirectional process that fits all organisations; it rather depends on a variety of organisational, strategic, and supply-chain related factors. to better illuminate these determinants and their influence on explaining the observed configurations, the study proposes the results of interviews with entrepreneurs and managers in a subset of firms from the sample. Qualitative evidence points to the importance of controlled and low-cost experiments, the integration of young talents in the marketing function of the firm, the existence of an explicit marketing strategy in the organisation, and the interaction between dedicated employees and external providers of digital services. Introduction the debate on firm competitiveness highlights the significant role of information and communication technology (ict). analysts and scholars welcomed it as an enabler of effective, flexible, and light forms of networked organisations (Pankowska, 2019). consumers’ propensity to become informed and shop online offers firms the opportunity to serve them better through precise profiling (li, 2016). Digital communication is relatively cost-effective, customised, and strengthens ties between firms and users (Finotto & Mauracher, 2020; Olson et al., 2021). the cOViD-19 pandemic has confirmed these trends (Bivona & cruz, 2021). Developing informative websites, communicating on social media, and managing online spaces that favour interactions and transactions with consumers proved to benefit firms in numerous industries. Food is a relevant sector for online communication because its products appeal to consumers through their physical and symbolic characteristics (russo & simeone, 2017). Previous research on online and digital marketing has examined consumer behaviour in digital spaces (calderon-Monge & ribeiro-soriano, 2023; kapoor et al., 2018). research on firms’ adoption and implementation of digital marketing tools and strategies is still fragmented and relatively underdeveloped (canovi & Pucciarelli, 2019). it is only recently that the food sector has been considered in specialized journals (Jia et al., 2022; tajvidi & tajvidi, 2021). as noted by Fernández-Uclés et al. (2023), studies covering these topics seldom offer a systematic perspective to understand how companies use different tools and combine them. they often focus on single platforms and instruments (chau et al., 2020) as standalone elements rather than as part of an integrated strategy. © 2024 the author(s). Published by informa uK Limited, trading as taylor & Francis group CONTACT Christine Mauracher [email protected] Department of Management, agrifood Management and innovation Lab, Ca’ Foscari university of Venice, Cannaregio 873, Venice 30121, italy https://doi.org/10.1080/23311975.2024.2398190 this is an open access article distributed under the terms of the Creative Commons attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. the terms on which this article has been published allow the posting of the accepted Manuscript in a repository by the author(s) or with their consent. ARTICLE HISTORY received 11 October 2023 revised 15 august 2024 accepted 23 august 2024 KEYWORDS Digital marketing; social media; social media marketing; digital presence; sMes; cluster analysis SUBJECTS Business, Management and accounting; industry & industrial studies; Marketing; entrepreneurship and small Business Management 2 F. checchinatO etal. research and industry experts agree that small and medium-sized enterprises (sMes) are slow to adopt digital tools for marketing and strategy. Various analyses offer a fragmented picture of the determinants of sMes’ hesitation in digital marketing. several mismatches have hampered the relationship between digital communication and small organisations. the clash between sMes’ operational logic and digital marketing strategies has been well-documented in research (colapinto et al., 2021). the absence of necessary skills (Bowen & Morris, 2019) and insufficient human resources (cassetta et al., 2020) contribute to delays in adopting digital tools for consumer outreach. Further investigations revealed that factors like limited technical or financial resources and a counterproductive organisational culture were impeding the digitalization of sMes (coco et al., 2024). the application of standardized, ‘one size fits all’ approaches in digital marketing might be another factor causing the divide between sMes and up-todate strategies (setkute & Dibb, 2022). this research contributes to the existing knowledge on digital and online marketing strategies for food sMes in multiple ways. First, it offers a granular and articulated definition of online presence that might integrate the fragmented assortment of constructs in the current literature. By considering the multitude of tools and channels at firms’ disposal, we expand the existing understanding of online presence. instead of progressing through a fixed set of stages, online presence can differ among various groups of firms. By utilizing a distinct dataset and an innovative analytic framework, we distinguish between the various configurations of firms’ digital presence. Moving from variables and models developed in extant literature and from our dataset, based on a sample of 520 agri-food sMes, we present different digital presence configurations. second, following the main prescriptions of the configuration approach (harms etal., 2009) this study sheds light on the determinants of patterns revealed by a cluster analysis. then, to understand the underlying factors influencing the observed setups, we rely on multiple interviews with managers and owners of food sMes and develop propositions for future research efforts. the following research questions are addressed. Which distinct configurations of firms’ online presence in the food sector can be identified? Which organisational, human, and structural factors explain firms’ online presence? Literature review Online presence to interact with customers and sell, businesses need to establish a presence in online spaces. Despite many mentions in the literature (checchinato & Zanichelli, 2016; kromidha & robson, 2020; lányi et al., 2021), the ‘concept of online presence is ill-defined’ (cioppi etal., 2019). One of the definitional issues is the ever-changing nature of the internet. Definitions predating the so-called web 2.0 are no longer applicable since they refer to websites, intranets, and portals without considering social networks (Bush etal., 1998). the terminology used to denote online spaces is also different: terms such as marketspaces, hypermedia communication environments, or e-markets were used in the early 2000s (Ozuem et al., 2008). currently, platforms, social networks, and social media dominate in terms of usage and academic research. the definition of online presence should acknowledge the options available to firms and how they are interconnected (kim et al., 2013). in essence, not only one needs to ponder the multiplicity of channels but also how firms can dwell in online environments: they might gain space (earned), control it (owned), or pay for it (through banners or sponsored campaigns) (colicev et al., 2018; Jayson et al., 2018). Feroz & Wood (2017) define online presence as ‘a multidimensional construct encompassing search engine visibility, social media presence, the level of incoming internet traffic to a retailer’s website (in-links) and its diversity (domain names), and the number of mentions a retailer’s name receives’. thus, they mix owned and earned media. smithson et al. (2011) classified presence into three dimensions: no website, website only, and website with e-commerce. studies of digital presence mainly considered owned media, detecting and measuring 1) websites, 2) social media pages on a single network, and 3) the co-existence of a website and a single social network page. Defining what is being measured is a critical question that must be addressed. if opening a social media page is relatively straightforward and inexpensive, consistently populating it is not (Valentini, cOgent BUsiness & ManageMent 3 2015). assessing presence while including consistency in content creation and engagement vis-à-vis the simple count of existing profiles challenges the existing knowledge base. Despite recognising the value of consumer engagement, brands often face challenges when it comes to investing in social media presence and maintaining consistent posting. thus, the chances of nurturing a brand community diminish, eroding the number of returning customers (sanders & Freberg, 2020). Online presence as a process Other viewpoints centre on the process that helps establish an online presence. it is framed as a stage-growth model, where businesses pass through different levels of digital proficiency to achieve superior marketing performances. several studies have represented this journey by enumerating the online tools required to strengthen brand image and interact with consumers. One of the first models was developed by Burgess and cooper (1998), a Model of internet commerce adoption (Mica). it was revised a few years later into an extended eMica (Daries etal., 2018) to fit the new digital environments. they postulated companies begin with a simple ‘presence’ on the web and build on functionalities over time, navigating through a learning process. Firms’ online presence becomes more complex as it incorporates new processes and initiatives originating from their experience with, and knowledge about, ict. as time passes, companies gain a better understanding of their customers through increased interaction and access to abundant information (kraus et al., 2019). this knowledge can be harnessed to revamp their online presence and to select adequate digital platforms to reach a better alignment with target audiences. the model provides a roadmap showing where a business stands in the process of developing e-commerce applications, moving from a static internet presence to a more interactive one. it comprises three stages: (1) promotion, (2) provision of information and services, denoting the level of interactivity, and (3) transaction processes. according to shaltoni & West (2010), a firm’s internet marketing strategy can lead to the redefinition of its overall strategy through three stages: communication, transaction, and transformation. in their analysis of sMes in the tourism sector, nakara et al. (2012) find that introducing social media into their operations triggers a pattern where, at the beginning, firms improvise and later proceed with careful planning and integration with the general marketing strategy. Focusing on social media, effing and spil (2016) propose three maturity stages related to the adoption and use of key elements of social media strategies: initiation, diffusion, and maturity (see also Pascucci et al., 2017). in summary, considerable research has focused on analysing web presence or social media presence. the construct lacks an integrative and parsimonious definition, while its measures are heterogeneous, making it difficult to capitalise on the accumulation of studies. Online digital presence: a conceptual framework to analyse sMes’ digital presence in an integrated and parsimonious way, we need to define its constitutive elements. shifting from the stages of growth of Burgess & cooper (1998), we transition to the eMica framework. We analysed the online presence of agri-food sMes, evaluating websites and social media, measuring the adoption of one or more owned media and also the consistency of firms’ activities and contents. We posit that publishing content and creating a fan base can lead to a higher level of maturity. the eMica model’s reliance on quantifying spaces does not allow a fine-grained assessment of firms’ online presence and the actual level of maturity: in fact, a profile (counted) might be empty or seldom populated, let alone visited and engaged with by users (Pascucci et al., 2017; shaltoni, 2017). We maintain that creating a website or opening a social network profile are the first steps; populating them with contents or generating and retaining traffic require awareness and explicit strategies. Our aim is to improve the model by including data on content creation frequency and its influence on the user base. this will provide a more accurate depiction of the original model’s second stage. Moreover, interactions are gained through the social media page, not a firm’s website; thus, we collected data on the presence of websites or social networks to monitor the static presence, frequency of publication, and fanbase performance to assess the interaction. 4 F. checchinatO etal. as other authors stated, no universally accepted method for evaluating online presence is available (Daries et al., 2018). to define various online presence configurations and build upon prior research (chung etal., 2017), we have identified five key areas. these areas encompass significant variables: website presence, social network presence, performance indicators (including editorial activities and engagement), international presence, and e-commerce. Descriptions of these five areas, of the variables, and of their roles in the framework are reported in the next paragraph. Methods We adopted a mixed-method research design to understand how food firms configure their online presence and explain the observed configurations. We collected and analysed data from various sources. First, as in gruner and Power (2018), we collected data from websites, social media pages, and profiles of a sample of italian food sMes. the dataset we analysed was built by coding the characteristics of the firms’ websites and online spaces, as illustrated in the following description of the analytic framework. no permission is required to use such data for research purposes. Following a configuration approach (harms et al., 2009), we treated these granular data to identify configurations of online presence in a cluster analysis that identified three clusters of firms. applying a cluster analysis, the most suitable approach is to discriminate among sets of units. cluster analysis sorts observations into similar groups and helps researchers create taxonomies that can validate new theories (crum etal., 2022). next, to triangulate data and get more insights, we chose a sub-group of respondents from firms’ managers and representatives. We conducted interviews with them to gain a deeper understanding of the organisational and strategic factors influencing their choices. this added depth to the quantitative analysis and configurations. We selected the informants based on considerations of variety and heterogeneity of the cases, as illustrated in the remainder of the paper. informed consent by interviewees was obtained when they were recruited for the interviews. interviewees were first contacted via email: the research team presented the study, its objectives and its contribution to practice. then, they were contacted via their publicly available corporate phone number or their private phone if they shared it in response to the original email. at the beginning of the call, the research team informed interviewees that the transcripts of their interviews would have been accessed and analysed only by the authors, and that excerpts of the interviews might be used only after being made anonymous. confidentiality of the data was ensured to all the respondents in written and oral form. after their oral agreement, the research team and the interviewees proceeded with the conversation, informing the interviewees that they could withdraw from the study at any moment (as in hasan etal., 2024). the questions formulated in the interview protocol aimed at collecting information on firms’ strategies rather than about people or their thoughts regarding themselves; no question delved with sensitive information or identifiable personal information. Based on this, the author team ruled out ethical risks but nonetheless they ensured that the research was designed and executed according to ethical and regulatory guidelines governing research involving human participants, with a particular attention to adapting the WMa declaration of helsinki (WMa, 2022) to a social investigation. Online presence data collection and measures We analysed a sample of italian sMes (10 to 250 employees) in the agri-food sector in the three regions of north-east of italy (Veneto, trentino - alto adige, and Friuli Venezia giulia). a commercial database, the Bureau Van Dijk’s repository aida, allowed us to extract the statistical universe. We kept all firms whose data on turnover and employees were available and complete. this procedure stabilised the final sample at 520 food companies. regarding measures, what follows is a description of the indicators denoting the variables of our model (table 1). Website presence to evaluate the basic level of online presence, we measured the existence of a company’s website (dummy variable). cOgent BUsiness & ManageMent 5 Social network presence We collected data on the presence of the company on the most used social networks: Facebook, twitter (now renamed as X), instagram, linkedin, Pinterest, and Youtube. For each, we created a dummy variable (1 when the firm had a profile or page on a specific social network, and 0 otherwise). We then created a variable to sum up these indicators of presence to provide information on the number of social networks a company adopted. Following the eMica model, we used these variables as measures of the intention to increase interaction with consumers. Social media performance since the simple presence or absence of a page or profile in social networks measures only partially a firm’s presence, we added four more variables to measure sMes’ social performance: two related to Facebook and two related to instagram. Firms’ activity on social networks activity metrics measure social media outputs in publishing content (tuten & solomon, 2017). creating a company account on a social network does not denote an active posture by the company: it might, in fact, remain silent. to measure social network activity, we gathered data on posting frequency on two main social networks: Facebook and instagram. We developed two strategies for data collection because of the differences in the algorithms and data availability. For the former, we collected data on the number of posts published in a six-month period (July-December). For instagram, we created an index by dividing the total number of posts by the number of years since the first post was published. Popularity on social networks in line with previous studies (e.g. Baghirov et al., 2019; kromidha & robson, 2020), we use the number of page/profile likes/fans to measure a firm’s ability to attract and engage users. Table 1. the analytic framework. Category Variable type of variable use of the variable in the model Website presence Website presence Dummy variable (1= presence; 0 = not present) Clustering variable social network presence social media presence on Facebook (FB), instagram (ig), Linkedin (LinK), twitter (tW), Youtube (Yt), Pinterest (Pin). Dummy variable for each social network (1= presence in the social network; 0 = not present) Clustering variable social network presence number of social media (n_social) Counting variable Clustering variable social media performance Firms’ activity on social network based on frequency posting on Facebook (FB_post) Counting variable Clustering variable social media performance Firms’ activity on social network based on frequency posting on instagram (ig_post) Counting variable Clustering variable social media performance Popularity on Facebook as number of Facebook page likes (FB_likes) Counting variable Clustering variable social media performance Popularity on instagram as number of ig profile followers (ig_followers) Counting variable Clustering variable international presence number of website languages (n_language) Counting variable Clustering variable e-commerce Proprietary e-commerce presence Dummy variable (1= presence; 0 = not present) Clustering variable experience in social networks usage numbers of years since the Facebook page or instagram profile has open (FB_years; ig_years) Counting variable Descriptive variable Firm size turnover Counting variable Descriptive variable Firm size number of employees Counting variable Descriptive variable sector Meat, Fish, Vegetables, oil, Dairy products, Cereals, Baked/pastry, others Dummy for each sector (1 = sector, 0 = otherwise) Descriptive variable 6 F. checchinatO etal. International presence We measured the number of languages used on firms’ websites; the higher the number of languages, the higher the hypothetical interactions with consumers (tang-taye & standing, 2016). translating the site also implies investing additional resources to reach a wider audience. E-commerce this is a dummy variable that measures the presence (or absence) of an e-commerce website in an owned space. then, we collected data to describe clusters in terms of size, subsectors, and experience in social network management. Firm size and Sub-sector We measured firm size in terms of turnover and employees. average firm size, especially in a sector like agri-food, might differ because of the specificities of the value chain. thus, operational and marketing logics can differ. Experience in social network use Firms’ digital maturity can increase as their digital seniority on social networks increases. Based on this assumption, we considered the number of years of presence in a social network as a proxy for this experience and accumulated learning. as suggested by Michaelidou et al. (2011), the timing of social media introduction may affect how companies use them. Baghirov et al. (2019) used a similar measure: Facebook fan page-opening time. We wanted to understand whether maturity is a matter of time and experience or if companies can begin their journey with a more mature configuration. Interviews as far as the interviews are concerned, to add depth to the different clusters and to uncover potential causal relationships, we interviewed 18 marketing and sales managers in a sub-sample of firms. We interviewed informants using questions that focused on the decision-making processes behind the observed configurations of food sMes’ online presence. We used a semi-structured script. Based on an analysis of the literature (effing & spil, 2016; li et al., 2021; Mergel & Bretschneider, 2013), we outlined an interview guide focusing on the following macro-themes: the objectives set for the online presence, the amount of dedicated resources, the methods used to manage and assess the results of digital presence, the actors involved in publishing and interacting online (e.g. internal teams vis-à-vis external agencies and consultants), and the factors behind top management decisions related to digital marketing strategies. We proceeded as follows. First, the selection of informants aimed at sectoral diversity. Firms and respondents, in fact, were selected across the sub-sectors represented in the sample. second, the research team ensured that firms with a noticeable online presence and organisations with a modest or limited presence were considered. interviews lasted approximately 1 hour and were transcribed and coded by the authors and a team of research assistants to validate the interpretation of the paragraphs (gioia et al., 2013). the authors then went iteratively through the codes and literature on digital marketing presence to create overarching categories and formulate research propositions. Results Sample description in our sample, websites are quite common (87% of the firms have at least one webpage). Facebook was the most popular social network (61%), followed by instagram (40%), linkedin (28%), and Youtube (28%). Only 15% of the companies operate owned e-commerce websites. cOgent BUsiness & ManageMent 7 Forty-one per cent of web contents are written in italian. eighteen per cent of the websites used two languages. the average number of languages used for the site is equal to 1.6 and 1.9 for social networks, with a range between 1 to 6. On Facebook, the average number of likes is approximately 5 thousand, while 20 is the mean value of published posts in the six months considered (table 2). the results show a high standard deviation in likes on Facebook page because of the high heterogeneity among the companies. this value is lower for instagram: it is less used, and we assume firms might use it in a more focused manner, thus resulting in more uniform behaviour. Cluster analysis We analysed the data to cluster firms into sets that discriminated their online presence by performing a hierarchical cluster analysis. We used the r statistical package. the clustering variables are listed in table 1. these variables substantiate our definition of online presence. We used the function Daisy: it provides a solution for computing the distance matrix when the data contains non-numeric columns (mixed data: the variables are quantitative continuous and dichotomous). among the different clustering criteria, we adopted agglomerative clustering, the most common type of hierarchical clustering used to group objects into clusters based on their similarity, known as agglomerative nesting (agnes). the algorithm initially treated each object as a singleton cluster. next, it merges pairs of clusters until all of them converge into a large cluster containing all objects, resulting in a tree-shaped representation (a dendrogram, Figure 1). Table 2. Clustering variables: descriptive statistics for each cluster (bold values are the highest for each row, the most significant). C1 C2 C3 sample average n = 121 (23%) n = 349 (67%) n = 50 (10%) n = 520 Pragmatists Laggards unfocused website 1 0.8 1 0.9 n_languages 2.2 1.4 1.7 1.6 FB 1 0.4 1 0.6 ig 10.2 0.7 0.4 tW 0.3 0 0.7 0.1 Pin 0.2 0 0.4 0.1 LinK 0.7 0.1 0.4 0.3 Yt 0.6 0.2 0.2 0.3 n_social 3.9 0.9 3.6 1.9 e-commerce 0.5 0 0 0.1 ig_post 67.6 7.3 39.3 24.4 ig_followers 2,106 96 720 642 FB_post 51 8 27 20 FB_like 17,156 748 8,015 5,265 Figure 1. Results of hierarchical cluster analysis. 14 F. checchinatO etal. References aswani, r., kar, a. k., ilavarasan, P. V., & Dwivedi, Y. k. (2018). search engine marketing is not all gold: insights from twitter and seOclerks. International Journal of Information Management, 38(1), 107–116. https://doi.org/10.1016/j. ijinfomgt.2017.07.005 Baghirov, F., Zhang, Y., & hashim, n. h. (2019). Facebook fan page management for global airlines. Tourism Review, 74(3), 532–546. https://doi.org/10.1108/tr-03-2018-0045 Berman, t., stuckler, D., schallmo, D., & kraus, s. (2023). 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