Team resilience in multiple project environments: What characteristics should be explored?

Eni, Yuli; Ichsan, Mohammad; Syamil, Ahmad; Trigunarsyah, Bambang Article Team resilience in multiple project environments: What characteristics should be explored? Global Business & Finance Review (GBFR) Provided in Cooperation with: People & Global Business Association (P&GBA), Seoul Suggested Citation: Eni, Yuli; Ichsan, Mohammad; Syamil, Ahmad; Trigunarsyah, Bambang (2024) : Team resilience in multiple project environments: What characteristics should be explored?, Global Business & Finance Review (GBFR), ISSN 2384-1648, People & Global Business Association (P&GBA), Seoul, Vol. 29, Iss. 5, pp. 133-145, https://doi.org/10.17549/gbfr.2024.29.5.133 This Version is available at: https://hdl.handle.net/10419/306004 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-nc/4.0/ I. Introduction Project management is on the rise, as indicated Received: Jan. 12, 2024; Revised: Feb. 20, 2024; Accepted: May. 1, 2024 † Corresponding author: Yuli Eni E-mail: [email protected] by the Talent Gap Report 2021 (Project Management Institute, 2021). The report predicts significant growth in total GDP of projected industries worldwide, from $24.7 trillion in 2019 to $34.5 trillion in 2030. The Information and Publishing sector shows the highest increase in the global Project Management Office Economy (PMOE), followed by Financial Services GLOBAL BUSINESS & FINANCE REVIEW, Volume. 29 Issue. 5 (JUNE 2024), 133-145 pISSN 1088-6931 / eISSN 2384-1648 Https://doi.org/10.17549/gbfr.2024.29.5.∣133 ⓒ2024 People and Global Business Association GLOBAL BUSINESS & FINANCE REVIEW www.gbfrjournal.org for financial sustainability and people-centered global business1) Team resilience in multiple project environments: What characteristic s should be explored? Y uli Eni a† , Mohammad Ichsan a , Ahmad Syamil b , Bambang Trigunarsyah c aManagement Program, Binus Business School Undergraduate Program, Bina Nusantara University, Jakarta, Indonesia bEntrepreneurship Program, Binus Business School Undergraduate Program, Bina Nusantara University, Jakarta, Indonesia cSchool of Property, Construction and Project Management, RMIT University, Melbourne, Australia A B S T R A C T Purpose: This paper aims to explore how project team members' resilience differs based on industry type, project budget, company type, and gender. Design/methodology/approach: Using the conservation of resources theory, this study focuses on exploring the insight of the gathered data from the perspective of descriptive statistics. To achieve this objective, a descriptive analysis was conducted using purposive sampling and snowball techniques, gathering data from 349 respondents. The collected data was analyzed using IBM SPSS software version 25. Findings: The study's results indicate that male respondents are dominant, primarily working in the construction industry, while female respondents tend to work in other industry sectors. Moreover, male respondents exhibited higher resilience scores, but no significant difference in resilience was observed based on gender. However, resilience levels varied according to the industry sector. Respondents from industries other than the construction sector tended to display higher resilience. Research limitations/implications: Considering that the study finds only minor variations, businesses in the same industrial sector might think about implementing a practice benchmark. Examining businesses outside of these important industries, however, may provide difficulties. Subsequent data-gathering endeavors may be broadened to encompass more industry sectors and subsequently scrutinized via case studies utilizing smaller samples from certain sectors. Originality/value: This study reveals that it is important to further expand and investigate these insights. Resources for team resilience, such as team confidence, a roadmap for teamwork, the ability to improvise as a team, and psychological safety for the team, can be added to future research. Furthermore, it is crucial to do quantitative research to look at how these elements show up in various industry sectors. Keywords: resilience, project management, multiple projects, descriptive analysis, project type Copyright: The Author(s). This is an Open Access journal distributed under the terms of the Creative Commons Attribution ⓒ N on-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution , and reproduction in any medium, provided the original work is properly cited. GLOBAL BUSINESS & FINANCE REVIEW, Volume. 29 Issue. 5 (JUNE 2024), 133-145 134 and Manufacturing/Construction. Additionally, the current work trend emphasizes team setups, increasing the number of people working on projects within the workplace. Project work is typically organized within teams. A team is defined as a group of interdependent individuals who share responsibilities and work towards a common goal (Moga, 2017). Working in a team is already challenging, given the diverse backgrounds and expertise of team members. The current working situation further complicates team interactions, particularly when team members work remotely. Furthermore, working on a project presents its own set of challenges. Changes are inevitable in project management (Killen et al., 2008a, 2008b, 2012; Killen & Hunt, 2010, 2013). In the project portfolio, the risks and uncertainties could lead to changes in the portfolio (Killen et al., 2008a, 2012; Killen & Hunt, 2010, 2013) as well as in the project individually (Besner & Hobbs, 2012; Ichsan et al., 2023; Project Management Institute, 2017; Saad & Asaad, 2015; Sanz & Ortiz-Marcos, 2019). From the perspective of the complexity of the projects, some aspects may add to further challenges and pressure to the project teams such as stakeholder and institutional factors (Dille et al., 2018; ElWakeel & Andersen, 2019), technology (Shenhar et al., 2005) and consideration of social and economic (Elia et al., 2020). Those conditions put pressure on the team members, making resilient teams critical in managing their projects. (Sharma & Sharma, 2016) opine that even though turbulence happens, resilient teams will more likely stay agile, innovative, and productive. A resilient team should have the ability to survive if they face adversity, while a non-resilient team will break down (Vera et al., 2017a). Hamsal et al (2022) argue that multiple perspectives, including individual, team, and organizational factors, influence a team's resilience. However, it is still necessary to explore whether team characteristics also influence team resilience. The current literature lacks an exploration of team characteristics such as size, gender, and establishment of team resilience. Yet, different team characteristics can moderate the level of team resilience. By knowing how they differ from their characteristics, the organization will establish different strategies to anticipate the level of resilience of the team where it is required. This study aims to examine the differences in team resilience based on the category of individual, project and organization characteristics. II. Literature Review Shean (2015) defines resilience as the capability of some people to have relatively good results despite severe stress or adversity, where their results are better than the results of others with the same experience. On the other side, Sharma and Sharma (2016) opine that resilience is the ability to recover from setbacks, deal positively, and adapt to major changes. Both definitions highlight two crucial aspects of resilience: the existence of adversities and the attainment of positive outcomes despite them. The concept of individual resilience is wellestablished, with studies linking behavioral capabilities, adaptive signaling, learning, and networking to individual resilience (Näswall et al., 2015). Employee resilience is known to have an impact on work engagement (Malik & Garg, 2020) and performance (Sobaih et al., 2021). McManus (2008) argues that employee resilience positively impacts organizational and community resilience. Furthermore, research by Norris et al. (2002) and Bonanno (2004) examines the development of resilience in individuals following a disaster, while Wang et al. (2020a) and Vindegaard and Benros (2020) shed light on people's resilience during the COVID-19 pandemic. The concept of organizational resilience is also well-established, with studies by Akgün & Keskin, (2014), Filimonau et al. (2020), Hamsal et al. (2022) exploring how organizational resilience influences performance. (Filimonau et al., 2020; Sin et al., 2017) Yuli Eni, Mohammad Ichsan, Ahmad Syamil, Bambang Trigunarsyah 135 and Hasayotin (2023) also link organizational resilience with organizational commitment. The development of organizational resilience has also been extensively studied, with key factors including leadership style (Buyl et al., 2019), HR policies and practices (Lengnick-Hall & Beck, 2005), and organizational processes (McManus, 2008) influencing organizational behavior. However, the concept of team resilience is still not well-established (Hartwig et al., 2020a; McEwen & Boyd, 2018). The definition of a team is a group of interdependent individuals who share responsibility and work towards a common goal (Moga, 2017). Team resilience is imperative because if the team fails to work effectively, it will have a damaging impact to the projects. They tend to be even more agile, innovative, and productive if they experience challenges (Sharma & Sharma, 2016). Teams that can emerge from challenging situations. They can adapt and manage in case of stress, and they tend to be more able to survive if they face difficulties (Sharma & Sharma, 2016). Akintunde-Adeyi et al. (2023), Hamsal et al., (2022) and Hamsal et al. (2022) describe team resilience as being influenced by multiple factors from different perspectives. In their research, they found that team resilience is positively and significantly influenced by individual resilience, team resources, team interactions, and organizational practices, nevertheless, transformational leadership does not have a significant impact on team resilience. Team resilience is also found that it has a positive and significant impact on team performance (Ji & Han, 2021). Despite a recent study, it is believed that there is a lack of studies linking gender with team resilience. However, studies exist that link gender with individual resilience. Most available studies focus on the link between individual resilience and gender. Studies by (Wang et al., 2020) and Vindegaard and Benros (2020), which highlight people's resilience during the COVID-19 pandemic, show that women are more prone to stress and therefore less resilient compared to their counterparts. Other studies by Norris et al., (2002) and Bonanno (2004) argue that gender can predict resilience after a disaster, with findings indicating that females are less resilient. The lower resilience of females may be attributed to their higher vulnerability to depression (Albert, 2015). The relationship between team size and team effectiveness has been studied previously. Studies by Giannoccaro et al. (2018) and Van Den Oever (2021) have shown that larger team size negatively affects team resilience. This may be because an effective team cannot be too big. Hackman and Vidmar (1970) state that the ideal team size is between 4 and 9 members, with an average of 4.6. Van Den Oever (2021) also suggests that team size influences the communication process, with larger teams leading to more complex communication. However, not all studies support the idea of an optimal team size. Guastello et al. (2019) suggest that the relationship is non-linear, as team resilience is also related to team workload and communication. Currently, there is limited research on the influence of project size on team resilience. However, studies have linked project complexity to resilience. Edmondson and Nembhard (2009) and Peñaloza et al. (2020) suggest that project complexity, together with cross-functional teams, temporary and fluid team membership, and embeddedness in organizational structures, can benefit team resilience. Peñaloza et al (2020) also confirms the positive effect of project complexity on team resilience. There is currently a lack of research examining the difference between category of gender, industry, type of companies, project budget and team resilience. Are certain industries more resilient than others? However, studies have shown that organizational structure influences the level of resilience. Van den Berg et al. (2022) states that structural forms of empowerment enhance individual and team resilience. When organizations empower their teams, it enhances team resilience. Some industries, such as the IT industry, arrange themselves to enable employees to become more empowered. However, traditional industries may still have heavily centralized decisionmaking processes. Another approach to predicting GLOBAL BUSINESS & FINANCE REVIEW, Volume. 29 Issue. 5 (JUNE 2024), 133-145 136 industry type and resilience is through the educational level. Studies have strongly confirmed how educational level increases individual resilience (Bonanno et al., 2007; Fiske et al., 2009; Seligman et al., 2009). Individual resilience, in turn, has an impact on team resilience (Hamsal et al., 2022). Knowledge-based industries, such as IT, often have more highly educated employees, while laborintensive industries may hire employees with lower levels of education. Based on the literature review, there are 42 indicators highlighted and required for this study as shown in Table 1 below. III. Methodology The design of this study is a quantitative and qualitative study. A set of structured questionnaires were established as research instruments using an online platform. A list of statements was established in the form of structured questionnaires to collect data between October and December 2021. The data was collected through an online survey, with researchers obtaining informed consent from the respondents prior to their participation. The questionnaires utilized a six-point Likert scale (from 1 strongly disagree to 6 strongly agree) was used ―― for participants to rate their opinion. With a six-point Likert scale, the mid-point is omitted to avoid a social desirability bias (Nadler et al., 2015). This study requires demographic data such as age, gender, educational background, service years, work location, industry, position, and size of the company, was also requested for descriptive analysis. Other demographic data such as years of experience, project location, industry type, and position were also included, however for this research, our focus of the study is to seek differences among categories such as gender, industry type, and type of companies. The targeted respondents were members of the project management team. Based on information on membership in professional project management organizations in Indonesia, the estimated population size was approximately 5,000 (Ikatan Ahli Manajemen Proyek Indonesia, 2020). Following the common approach suggested by (Hair et al., 2019) where the number Constructs No Code Explanation Reference Employee Resilience 1 EMRS01 Effective collaboration with others to manage challenges at work (Tonkin, 2016) 2 EMRS02 Managing high workload for long periods of time successfully. 3 EMRS03 Resolving challenges using competence at work 4 EMRS04 Re-evaluation of work performance and continuous improvement of the ways of working. 5 EMRS05 Effective responses to negative and positive feedback. 6 EMRS06 Seeking assistance when specific resources are required. 7 EMRS07 Approaching managers if support is needed. 8 EMRS08 Using changes as an opportunity to grow. 9 EMRS09 Learning from mistakes at work and improving them. Table 1. Research constructs and items Yuli Eni, Mohammad Ichsan, Ahmad Syamil, Bambang Trigunarsyah 137 Constructs No Code Explanation Reference Effective Team Interaction 1 TINT01 Closed relationships among team members (Sharma & Sharma, 2016) 2 TINT02 Effective communication among team members 3 TINT03 Sharing necessary information among team members 4 TINT04 Using common terms among team members for work at work 5 TINT05 Agreement on how they are expected to behave against each other Team Resources 1 TRES01 The right size of team to accomplish the work (Sharma & Sharma, 2016) 2 TRES03 Each team member has a specific skills to work as a team 3 TRES04 The organization provides what the team needs to manage the project. (Vera et al., 2017b) 4 TRES05 Enough sources for gain information and provide feedback. Transformational Leadership 1 TFRL01 Leaders provide priorities to new opportunities in the organization. (Aragon-Correa et al., 2007); (Chen et al., 2016) 2 TFRL02 Leaders provide clear communication about short-term goals. 3 TFRL03 Leaders give people motivations more than controlling the company 4 TFRL04 Leaders play a significant role in company operations. 5 TFRL05 Leaders do coordination with them for decision-making. 6 TFRL06 Leaders provide new perspective in problem solving. Organizational Practices 1 ORPR01 Availability of support whenever help is needed. (Tonkin, 2016); (Vera et al., 2017b) 2 ORPR02 Organization notices of great people's accomplishment. 3 ORPR03 People's opinions are taken care by the organization 4 ORPR04 Work-life balance are implemented in the organization 5 ORPR05 People's skill development is provided 6 ORPR06 People's career development is provided 7 ORPR07 People's wellbeing is taken care 8 ORPR08 Equity is provided by the organization 9 ORPR09 Open communication is encouraged by the organization Table 1. Continued GLOBAL BUSINESS & FINANCE REVIEW, Volume. 29 Issue. 5 (JUNE 2024), 133-145 138 of samples is around five times the number of indicators, this study used 42 indicators, as highlighted in Table 1, requiring a minimum of 210 samples as proposed by Hair et al., (2019). For this particular study, the analysis was done using seven indicators from the construct Team Resilience. The sampling techniques employed was purposive sampling and the snowball method. The questionnaire was distributed as an online survey through various online media platforms, with respondents encouraged to share it with other potential respondents in their network to gather related data on variables. It is important to note that using this method, there may have been a potential for common method bias (CMB), which could have influenced the data. The data are further analyzed using SPSS 25 mainly using descriptive analysis and cross tabs. IV. Results and Discussion A total of 354 respondents participated in the survey; however, only the data of 349 respondents are considered eligible to proceed to the next step for further analysis. The first step involves analyzing the data to explore its demographic characteristics. The results of this analysis are presented in Table 2. Table 2 reveals that the majority of respondents are from the construction industry sector, followed by information technology and communication (ICT), and then other various sectors. The "other" sector includes consulting, financial services, manufacturing, oil & gas, and other smaller sectors. Most of the respondents hold managerial positions and are male. The respondents are involved in projects located outside Jakarta but within Java Island. Descriptive analysis has been conducted to determine the central tendency, dispersion, and distribution of the data. Constructs No Code Explanation Reference Team Resilience 1 TRES01 Being positive and move forward whenever facing pains. (Mallak, 1998) 2 TRES02 Changes are perceived positively and allow adaptation 3 TRES03 Having access to resources for adaptive responses. 4 TRES04 Decision making authority and use of resources are provided to support adaptive responses 4 TRES05 Development to the ability to create solutions whenever challenges are faced. 6 TRES06 Development to the decision-making ability with limited information. 7 TRES07 Sharing an understanding of teams' mission and using it if required to work smoothly Team Performance 1 TPER01 Ability to work properly in the event of unexpected situation. (Hartwig et al., 2020b); (Vera et al., 2017b) 2 TPER02 Experience facing adversity with good outcome. 3 TPER03 Well-functioning team during adversity Source: Research Data from various literatures. Table 1. Continued Yuli Eni, Mohammad Ichsan, Ahmad Syamil, Bambang Trigunarsyah 139 Variables such as gender, industry sector, company type, and project budget have been analyzed, as they will be used for further analysis using crosstabulation. The descriptive analysis was conducted using three variables intended for further cross-tabulation analysis, and the results are presented in Table 3. From Table 3, it is evident that the data does not appear to follow a normal distribution. The non-normal distribution of the data leads to heterogeneous variances, which indicates that the variables used exhibit uneven distribution of data. As a result, the outcomes may be skewed towards certain aspects of the variables under study. When data is non-normal, it means that its distribution deviates from a normal (or Gaussian) curve. Consequently, some statistical methods that rely on the assumption of normality may not provide accurate results. There are several impacts of non-normal data, including: a. Errors in hypothesis testing: Hypothesis testing often assumes that data is derived from a Variables nRMnMx Mean SD Var Skew Kurtosis Stat St.Er Stat St.Er Stat St.Er Stat St.Er Gender 349 1 1 2 1.19 0.02 0.39 0.16 1.57 0.13 0.47 0.26 Ind_Sector 349 2 1 3 1.83 0.04 0.82 0.68 0.32 0.13 -1.46 0.26 Comp_Type 349 3 1 4 2.05 0.05 0.87 0.76 0.72 0.13 0.02 0.26 Budget 349 3 1 4 2.63 0.07 1.30 1.70 -0.14 0.13 -1.72 0.26 Source: Research Data Note: n = Number of samples; R = Range; Mn = Minimum; Mx = Maximum; Stat = Statistics; SE = Standard Error; SD = Standard Deviation; Skew = Skewness; Comp_Type = Company Type; Ind_Sector = Industry Sector Table 3. Descriptive statistics No Demographic Profile n(%) 1. Gender Male 282 81% Female 67 19% 2 Industry Sector Construction 152 44% Information & Communication Tech. (ICT) 103 30% Others 94 26% 3. Position Business owner or C-Suites 15 4% Senior managers or managers 181 52% Supervisors or team leaders 59 17% Staffs level 74 21% Others 20 6% 4. Location Jakarta 61 17% Outside Jakarta but in Java Island 210 60% Outside Java Island 78 22% Source: Research Data Table 2. Data demography GLOBAL BUSINESS & FINANCE REVIEW, Volume. 29 Issue. 5 (JUNE 2024), 133-145 140 population with a normal distribution. However, if the data deviates from normality, conducting hypothesis tests may lead to inaccurate results. b. Errors in parameter estimation: Many statistical techniques, such as regression analysis and analysis of variance, rely on the assumption of normality in the underlying population. When the data does not follow a normal distribution, the estimated parameters obtained from these techniques may lack accuracy. c. Increased influence of outliers: In non-normal data, outliers or extreme values may have a more significant impact on the results of statistical analysis. These outliers can skew the data and potentially affect the interpretation of the findings. d. Difficulty in comparing data: When comparing means or variances between two or more groups, the assumption of normality is often required. If the data from these groups does not adhere to a normal distribution, making accurate comparisons becomes challenging or unreliable. However, there are instances where non-parametric methods can be employed to analyze non-normal data. These methods rely on ranking or comparing data, eliminating the need for assumptions about the data distribution. Once the descriptive analysis is completed, further cross-tabulation analysis is conducted, as shown in Table 3. The objective of this cross-tabulation is to explore the data distribution across different categories of industry sectors, project budget values, and the number of projects within organizations. Based on Table 4, it is evident that the majority of respondents in the construction sector have the highest number of projects (29% of total respondents) with a project budget value exceeding 100 billion IDR, as compared to the ICT and other sectors. Additionally, 43 respondents are affiliated with organizations involved in more than 10 projects during their tenure. This trend appears to be consistent across other industry sectors as well. Conversely, most respondents in the ICT sector are associated with project organizations that have a project budget value Industry Type Number of projects Total First project 1 to 5 projects 5 to 10 projects More than 10 projects Construction Project budget Less than 10 Billion IDR /BIDR (small projects) 1 1 0 7 18 10 to 50 BIDR (small to medium projects) 3 3 1 9 17 50 to 100 BIDR (medium to big projects) 3 3 1 9 17 More than 100 BIDR (big projects) 29 29 4 43 100 Total 42 36 6 68 152 Information and Communication Technology (ICT) Project budget Less than 10 BIDR (small projects) 12 12 1 21 43 10 to 50 BIDR (small to medium projects) 8 8 0 10 21 50 to 100 BIDR (medium to big projects) 3 3 0 5 11 More than 100 BIDR (big projects) 1 1 0 25 28 Total 17 24 1 61 103 Others Project budget Less than 10 BIDR (small projects) 11 11 11 16 49 10 to 50 BIDR (small to medium projects) 1 1 1 8 17 50 to 100 BIDR (medium to big projects) 2 2 2 7 11 More than 100 BIDR (big projects) 1 1 1 11 17 Total 22 15 15 42 94 Source: Research Data Table 4. Cross-tabulation of industry type and project budget.