Covariance-based Structural Equation Modeling Research Articles

The silver lining of supply chain complexity: building supply chain resilience and robustness through exploitation and exploration

PurposeThis study aims to analyse whether the presence of supply chain complexity (SCC) influences firms to improve their supply chain (SC) resilience and SC robustness capability. This study also examines an important paradox: whether investing in both exploitation and exploration practices is conflicting or complementary to enabling SC resilience and robustness in the presence of SCC.Design/methodology/approachThe authors used a survey-based approach to collect 242 useful responses from SC professionals of Pakistani firms, an important emerging economy context. The data were analysed with covariance-based structural equation modelling to statistically validate the model.FindingsThe analysis reveals several key findings: the presence of SCC has a direct, positive influence on SC resilience and SC robustness; while exploitation practices only partially mediate the nexus between SCC and SC resilience, they fully mediate the relationship between SCC and SC robustness; while exploration practices partially mediate the nexus between SCC and SC resilience, they do not mediate the relationship between SCC and SC robustness and SCC has a significant influence on SC resilience and SC robustness sequentially through exploitation and exploration (i.e. one after the other).Practical implicationsThese findings help to reconcile the exploitation versus exploration paradox in cultivating SC resilience and SC robustness in the presence of SCC. The findings assist SC managers in determining how to deploy their limited resources most effectively to enhance SC resilience and SC robustness while facing SCC.Originality/valueThe authors devise and empirically validate a unique framework that demonstrates how the presence of SCC works as a stimulus to build SC resilience and SC robustness.

Unveiling the impact of carbon-neutral policies on vital resources in Industry 4.0 driven smart manufacturing: A data-driven investigation

The study aims to empirically examine the effect of carbon-neutrality policies on the key resources needed for Industry 4.0 driven smart manufacturing and how these resources can provide a sustainable competitive advantage. The theoretical framework is integrated with the institutional theory and the resource-based view (RBV). The empirical method is used for collecting data through surveys and further covariance-based structural equation modeling is used to test the hypotheses. Findings indicate that carbon–neutral-based government policies have a stronger influence on tangible resources and human skills than intangible resources related to Industry 4.0 driven smart manufacturing. Second, carbon–neutral policy alignment with the firm’s sustainability objectives plays a moderating effect on the relationship between carbon–neutral-based government policies and resources (tangible, intangible resources and human skills) for Industry 4.0 driven smart manufacturing. Lastly, the three resources (tangible, intangible resources and human skills) for Industry 4.0 driven smart manufacturing play a critical role in developing firms’ carbon–neutral capability and further enhancing operational performance. Managerial implications include investment in advanced digital technologies, developing a strong mindset among employees and supply chain stakeholders, and designing training programs for enhancing smart manufacturing performance to develop carbon-neutrality capability. This study proposes a hybrid theory in the context of carbon neutrality by integrating institutional theory and RBV. This is the first study that examines the effect of carbon neutrality-based government policies on vital Industry 4.0-driven smart manufacturing resources and the indirect effect on carbon neutrality capability and operational performance.

Nexus between e-service quality and e-customer satisfaction through functional and hedonic values: case of online shopping in Pakistan

PurposeThe concept of online shopping has been in vogue for the past two decades and is on the rise. Even developing countries like Pakistan are using electronic platforms to buy and sell goods and services, and the trend has been increasing ever since the COVID-19 pandemic. Drawing on the expectancy-disconfirmation theory, this study aims to test the e-service quality (E-SQ) and e-customer satisfaction (ECS) linkage with the mediating roles of functional values (FVs) and hedonic values (HVs).Design/methodology/approachThe data have been collected from 298 customers of AliExpress and Daraz e-commerce platforms and analyzed using covariance-based structural equation modeling (CB-SEM).FindingsThe results of the study showed a significant positive relationship between E-SQ and ECS and indirect linkage through FVs and HVs have also been established.Practical implicationsE-commerce platforms, particularly in Pakistan, should place a strong emphasis on FVs by providing accurate product details, user-friendly navigation, transparent pricing and streamlined transactions. Customers' trust and confidence will increase if they have a smooth and effective online purchasing experience. Customer satisfaction may be influenced by regular platform functionality and usability changes.Originality/valueThe use of functional and HVs is considered to be a novel factor in testing the relationship between E-SQ and ECS.

Psychological wellbeing and avoidance strategies as moderators between excessive social media use and academic performance among Indian college students

PurposeThis study aims to assess the negative aspect of social media use among college students in India. A conceptual model showing the relationship between excessive social media use (ESMU) and academic performance of college students has been developed and tested. Further, the moderating role of psychological well-being and avoidance strategies were investigated.Design/methodology/approachA survey instrument was developed, and data was collected from 557 college students from higher educational institutions in southern India. First, the psychometric properties of the measures were tested using the Lisrel software for covariance-based structural equation modeling. Second, the structural model was tested by using PROCESS macros.FindingsThe results reveal that ESMU is a precursor to anxiety and academic performance. The findings also indicate that anxiety mediates the relationship between ESMU and academic performance. Psychological well-being and avoidance strategies were significant moderators in the relationship between ESMU and anxiety.Originality/valueThe multi-layered conceptual model was developed and tested in the context of a developing country (India) and investigated the effect of ESMU by college students on their academic performance and anxiety. The three-way interaction between psychological well-being (first moderator), avoidance strategies (second moderator) and ESMU influencing academic performance mediated through anxiety is studied in this research. To the best of the authors’ knowledge, such a moderated moderated-mediation in connection with social media use is a unique contribution of this study.

Factors influencing acceptance of Indonesian contact tracing APP: Development of the technology acceptance model

Contact tracing apps for the COVID-19 have been broadly developed worldwide and Indonesia is no exception. The Indonesian application is called PeduliLindungi. This study aimed to provide a comprehensive understading of the public’s intention to use such applications by incorporating trust, trust in government, privacy concerns, and social influence variables as an extension to the technology acceptance model (TAM). A questionnaire was distributed online through social media to attain 371 participants among Indonesian inhabitants based on the convenience sampling method. Descriptive analysis and covariance-based structural equation modeling were used to analyze the data. The results indicated that intention was predicted well by trust, attitude, and social influence. Furthermore, trust in government played a role in predicting the application’s trustworthiness. The government and decision-makers should consider this observation in promoting the PeduliLindungi application, as it could increase its effectiveness.

The roles of LinkedIn-based skill endorsements and LinkedIn-based hiring recommendations on hiring preferences: evidence from Bangladeshi employers

Purpose LinkedIn is a popular and maybe the best job-oriented social networking site (SNS) around the world. Numerous individuals (mostly, jobseekers), as well as the companies (mostly, hiring organizations) have LinkedIn accounts. This study intends to reveal the roles of LinkedIn-based skill endorsements (LSEs) as well as LinkedIn-based hiring recommendations (LHRs) on the hiring preferences (HPs) of Bangladeshi employers. Design/methodology/approach The authors purposefully selected 388 valid respondents (employers) from different Bangladeshi job sectors. Based on their responses, the authors applied SPSS 25 for explanatory statistics and a “Covariance-based Structural Equation Modeling (CB-SEM)” (with AMOS 25) to measure the hypothesized associations. Findings After appropriate analysis, the authors revealed a momentous positive role of LHR on HP, whereas LSE was identified to have an inconsiderable role on HP. Originality/value In this empirical study, the authors tried to highlight the relatively unattended area of Bangladeshi employers' HPs that can be affected by LSEs and LHRs. The authors believe that this study will encourage the researchers to unveil the impacts of LinkedIn-based profile characteristics on job candidates' employability. This empirical study can also aid the employers and policymakers to look for a new avenue for hiring competent talents.

Unveiling the Dynamics of Expectation, Flow, Enjoyment, and Satisfaction: Drivers of Continued Subscription Intentions Among Netflix Users

"Research Aims: This study investigates the determinants impacting the intention of Netflix users to continue using the platform. By leveraging the extended Expectation-Confirmation Model of continued IT usage and hedonic variables, including Confirmation, Flow, Perceived Usefulness, Perceived Enjoyment, and Satisfaction, the research aims to discern the most influential factors. Design/Methodology/Approach: The research recruited 271 participants through non-probabilistic purposive sampling, targeting Indonesian Netflix subscribers active within the preceding six months who were at least 17 years old at the time of the study. Covariance-based Structural Equation Modelling was employed to analyse the collected data. Research Findings: User enjoyment and Satisfaction mediate the relationships between Flow and Confirmation with Netflix's continuance intention. Flow emerges as the preeminent determinant of continuance intention among the exogenous variables. While Flow's influence on continuance intention is mediated by Satisfaction and Enjoyment, there is no direct effect between Flow and Satisfaction. Perceived Usefulness exhibits no substantial correlation with continuance intention. Theoretical Contribution/Originality: This research underscores the pivotal role of Flow in driving enjoyment and continuance intention within video subscription services like Netflix. Managerial Implications in the South East Asian Context: The study offers insights into the preferences and behaviours of Netflix users in the Southeast Asian context, employing Indonesia as a focal point. This valuable information equips Netflix and other regional SVOD providers to strategically enhance their offerings and services. Research Limitations & Implications: To enhance the robustness of the findings, future research should encompass broader and more diverse populations for comparative purposes. Including new variables, such as digital piracy and perceived ease of use, would contribute to a comprehensive understanding of the dynamics at play. Keywords: Technology Acceptance Model, Expectation Confirmation Model, Flow, Continuance Intention, Netflix"

Critical components for successful BIM-based sustainable building design collaboration: structural equation model analysis

Purpose The efficient application of building information modeling (BIM) methodology in the sustainable building design process, known as green BIM, provides ideal leverage to significantly enhance multidiscipline team collaboration. However, the practical execution of green BIM is characterized by issues such as duplication of work, information silos and poor cross-party coordination. Besides, there are limited studies on the specific components that are critical to driving green BIM collaborative design. This study aims to establish the critical components of green BIM collaborative design to enable the multidiscipline team to effectively use diverse software to collaboratively exchange accurate information, thus ensuring informed decision-making in the sustainable building design process. Design/methodology/approach Data were obtained by using a questionnaire to survey 360 respondents comprising mainly architects and engineers (civil, mechanical and electrical) in Malaysia. Subsequently, data were analyzed via confirmatory factor analysis. Afterward, a measurement model was established and used to test the 11 hypotheses of this study. Findings A covariance-based structural equation model of the critical components for successful BIM-based sustainable building design collaboration was established. Practical implications The research findings will guide the multidisciplinary team to collaboratively exchange accurate information in green BIM practices. Originality/value To the best of the authors’ knowledge, this research is the first attempt in the literature to provide a pragmatic approach for practitioners to combine the established critical components of green BIM to collaboratively exchange heterogeneous sustainability criteria and efficiently design buildings with high sustainability performance, particularly in emerging countries like Malaysia.

Psychological capital and multifaceted nature of job performance: mediation by intrinsic motivation and goal-commitment

PurposeThe researchers aim to investigate the role of psychological capital (PsyCap) in facilitating intrinsic motivation and goal-commitment among employees at the workplace, affecting outcome variables, namely, in-role and extra-role job performance.Design/methodology/approachData were collected from 640 employees working in the information technology sector of India. Covariance-based structural equation modeling (CB-SEM) was used to test the hypothesized relationships.FindingsAnalysis revealed a significant positive impact of PsyCap on the two behavioral facets of job performance. Intrinsic motivation and goal-commitment were found mediating the influence of PsyCap on the two facets of job performance.Practical implicationsThe information technology sector is characterised by continuous change. It requires voluntary prosocial behavior from employees, where the employees are expected to display multifaceted job performance behaviors, where they go beyond their job duties to cater for the dynamics of the IT sector. The present study provides means by which intrinsic motivated and goal-committed behavior are facilitated for both the in-role and extra-role job performance.Originality/valueThe present study is among the few preliminary studies that have provided evidence that intrinsic motivation and goal-commitment are the two variables which aid PsyCap in predicting both the prescribed and voluntary job performance behaviors.

Disentangling consumers’ negative reactions to impulse buying in the context of in-app purchase: Insights from the affect-behavior-cognition model

Deciphering how consumers react to impulse purchases is vital for sellers to bolster consumers’ post-purchase experience and induce subsequent purchase behavior. Contextualized to in-app purchases, this study draws on the Affect-Behavior-Cognition (ABC) model to disentangle the relationships among distinct categories of negative post-purchase reactions and the moderating influence of product appeal on these relationships. Empirical data was collected from an online survey of 376 in-app buyers and Covariance-Based Structural Equation Modelling (CB-SEM) was employed to validate the research model. Analytical results indicate that awareness of breakdown in self-control exerts a positive effect on post-purchase regret while regret positively impact the negative emotions of anger and guilt, both of which in turn drive the concealment of purchased good or service. In-app product appeal is discovered to reinforce the relationships between regret and anger/guilt as well as the relationship between anger and concealment while simultaneously attenuating the relationship between guilt and concealment. This study sheds light on impulsive in-app purchases by delivering a deeper understanding of the interdependencies among constituent post-purchase reactions in the context of in-app impulse buying.

Why do consumers consume masstige products? A cross-cultural investigation through the lens of self-determination theory

Shaping consumers' attitudes and influencing their consumption of masstige brands via intrinsic and extrinsic motivation is an unexplored research area. By applying self-determination theory, this study attempts to divulge how extrinsic and intrinsic motivations in a cross-cultural context affect masstige consumption behavior. Thus, a research framework and hypotheses are developed and validated using cross-sectional research. The data were collected from 437 Canadian and 412 Indian respondents using Amazon Mechanical Turk. Path analysis was performed using covariance-based structural equation modeling (CB-SEM) to test the hypothesized relationship. The path analysis established that attitudes and masstige consumption are influenced by both extrinsic and intrinsic motivations and further studies established that attitude partially mediates the effect of extrinsic and intrinsic motivations on masstige consumption. However, the moderation analysis failed to establish the role of Hofstede's cultural variable (i.e., power distance) in modifying the effect of extrinsic and intrinsic motivation on masstige consumption for Indian consumers, while it did in the Canadian context, albeit on select relationships. The findings of this study may be useful to masstige marketers in understanding cultural differences when designing promotional campaigns that resonate with consumers.

Investigating how consumer-perceived value and store image influence brand loyalty in emerging markets

PurposeThis study examines the impact of consumer-perceived value (CPV) dimensions such as product quality, price fairness, brand prestige and brand positioning on brand attitude and loyalty for electronic home appliance brands in an emerging market. It also explores the moderating effect of perceived store image on the relationship between brand attitude and loyalty.Design/methodology/approachThis study proposes an integrated model based on consumption values and the value-attitude-behavior (V-A-B) framework. Survey data from 209 Bangladeshi consumers of electronic home appliances were used to test the model. Covariance-based structural equation modeling (CB-SEM) and PROCESS macro were employed to test the hypotheses.FindingsThis research underscores the importance of CPV dimensions, such as product quality, price fairness, brand prestige and positioning, in predicting brand loyalty through brand attitude. Store image moderates the link between brand attitude and loyalty, with a stronger relationship when store image is high and a weaker relationship when it is low.Originality/valueThis study broadens marketing and consumption value theory by investigating brand prestige and positioning in the V-A-B framework in the emerging market. This is the first study to use perceived store image to moderate the relationship between brand attitude and loyalty.

Consumer engagement with restaurant brands on Instagram: the mediating role of consumer-related factors

PurposeConsumers’ digital engagement can bring various benefits to both brands and consumers. Besides, few studies investigated the outcomes of engagement with restaurant brands on Instagram. Therefore, this study aims to examine the effect of consumer engagement (CE) with restaurant brands on consumer-related factors (namely, consumer’s brand knowledge, perceived enjoyment and consumer social interaction) and brand-related factors (namely, e-WOM and brand reputation), as well as the mediating role of consumer-related factors.Design/methodology/approachThe sample consisted of 394 Instagram followers of restaurant/coffee shop brands, and covariance-based structural equation modeling and bootstrapping were used to assess the hypothesized relationships.FindingsThe results show that CE with restaurant brands on Instagram enhances brand-related outcomes as well as consumer-related outcomes. Moreover, consumer-related factors partially mediate these relationships.Practical implicationsThe findings of this study provide insights for restaurant managers and digital marketers to stimulate consumer-brand engagement.Originality/valueTo the best of the authors’ knowledge, this study is among the first that examines the effect of CE with restaurant brands on consumer- and brand-related outcomes on Instagram. The context of the study is Iran, which adds to the literature on CE that mainly focuses on developed countries.

WHY DO CONSUMERS PURCHASE IMPORTED HALAL MEAT PRODUCTS?

Halal meat is important in Indonesia, not only because of the Muslim consumer’s demand but also because of the low domestic production. Therefore, this study aims to determine the factors that influence the intention to purchase imported halal meat from Muslim consumers in Indonesia. To answer the inquiry, it employed a quantitative research method and adopted the Theory of Planned Behavior and Push-Pull Mooring Theory. Primary data was obtained from 913 Indonesian Muslim respondents and analyzed using Covariance-Based Structural Equation Modeling (CB-SEM). The results showed that nutritional content, behavioural control, and attitudes significantly and positively affect the intention of purchasing imported halal meat products. Meanwhile, the price variable significantly negatively affects the purchase intention. The religiosity variable, which acts as a mediating variable, significantly positively affects attitudes to buying imported halal meat products. Meanwhile, the variables of subjective norms, sensory attractiveness, and halal awareness are not significant in this study. The results are expected to provide insights for halal meat importers, halal industry players, the government and other stakeholders in Indonesia and globally.

The Dark Side of Empowering Leadership: How Empowering Leadership Affects Unethical Pro-Organizational Behavior in Construction Projects

The success of construction projects heavily depends on the compliance of parties with ethical codes of conduct. Unethical pro-organizational behavior (UPB) may serve as a barrier to close collaboration between parties. Although empowering leadership is generally considered to be beneficial to project management, this study argues that empowering leadership may unintentionally increase the tendency of employees to adopt UPB. The aim of this study is to uncover the influencing mechanism underlying empowering leadership and UPB by introducing the mediating role of role stress. It is hypothesized that empowering leadership can enhance employees’ role stress, thereby increasing the engagement of UPB. Moreover, organizational goal clarity can ease the negative effect of empowering leadership. With data collected from experienced construction professionals, the results of the covariance-based structural equation modeling (CB-SEM) supported the hypothesis. The findings help in understanding why employees may adopt unethical behaviors when they feel high levels of role stress that are caused by empowerment. Theoretically, the study enriches the literature on empowering leadership and UPB in the construction context. In practice, managers are reminded about the adverse effect of empowering leadership on employees’ unethical behaviors. Organizational management tools are suggested to assist in assigning work appropriate to employees’ roles. Regular checks and feedback about organizational goals are also necessary to confirm compliant behaviors and progress.

Drivers of generative artificial intelligence to fostering exploitative and exploratory innovation: A TOE framework

This research work aims to investigate the antecedents of generative artificial intelligence (GEN-AI) adoption, and exploratory and exploitative innovation. A conceptual model based on the technology-organization-environment (TOE) framework is proposed and tested empirically using online survey-based data collected from 260 managers and administrative employees located in the Jordanian retailing industry. To achieve the objectives of this work a covariance-based- structural equation modelling (CB-SEM) was employed. The results indicate that relative advantage, top management support, organizational readiness, and customer pressures positively influence GEN-AI adoption. The empirical results demonstrated that the influence of compatibility and competitive pressures on GEN-AI adoption are insignificant. It was found that complexity negatively influence of GEN-AI adoption, also the findings confirm the positive impact of GEN-AI on both exploratory and exploitative innovation. The findings of the existing research would be valuable for GEN-AI technology providers, managers and top management in the retail firms sector in terms of building effective procedures to promote the successful adoption of GEN-AI technologies and innovation.

Why residents exhibit environmentally responsible behavior?

The main objective of the current research was to propose and validate an integral model encompassing mindfulness, enjoyment of nature, community attachment, community involvement, sustainable attitude, place attachment, and environmentally responsible behavior with the support of attitude–behavior theory. Measurement and structural models of the study were tested using covariance-based structural equation modeling with the help of 385 sample data. Mindfulness was discovered as the most important predictor of a sustainable attitude followed by community involvement, enjoyment of nature, and community attachment. Further, empirical findings discovered a positive and significant effect of residents' sustainable attitude on their place attachment. Finally, the study model confirmed residents’ place attachment as more important predictor of their environmentally responsible behavior than sustainable attitude. Proposals for future study areas and implications for destination managers and policymakers are reported.

Apparel behavioural intentions of urban bottom-of-the-pyramid consumers: exploring the role of store atmospherics

Purpose This study aims to explore the impact of store atmospherics on urban bottom-of-the-pyramid consumers’ behavioural intentions to purchase apparel in an emerging African market context. This study also considers purchase antecedents to attitude, perceived behavioural control and social norms as determinants of urban bottom-of-the-pyramid consumers’ apparel behavioural intentions. Design/methodology/approach Using non-probability sampling, specifically purposive and interlocking sampling, data collection was secured from 881 economically active Namibian urban bottom-of-the-pyramid respondents through interviewer-administered questionnaires. Covariance-based structural equation modelling assessed the significant relationships among all constructs in the conceptual model. Findings This study found that for favourable apparel behavioural intentions of urban bottom-of-the-pyramid consumers to occur, apparel retailers should emphasise trust, perceived awareness and self-identity through apparel assortment and groupings, easy-to-read visible signage, together with competent, friendly and respectful sales personnel in their store atmospherics. Practical implications The findings of this study may guide apparel retailers in other emerging African markets to develop regional integration, market-based solutions and inclusive economic growth focusing on “non-essential” products, such as apparel, among urban bottom-of-the-pyramid consumers. Originality/value This study expands the intellectual boundaries of urban bottom-of-the-pyramid consumers’ behavioural intentions towards “non-essential” products. The theoretical framework supports the integration of both the stimulus-organism-response model and the theory of planned behaviour into one single model for empirical investigation. Additionally, adopting a novel theoretical framework helped identify the impact of store atmospherics from a bottom-of-the-pyramid perspective in an emerging African market context, such as Namibia.

Beyond Factors: IGSCA-SEM’s Application in The Context of Cannabis Tourism

Structural Equation Modeling (SEM) is a statistical technique that is used to model the relationships among hypothetical constructs investigated by researchers. SEM can be broadly classified into two main approaches: factor-based (or covariance-based) SEM and component-based (or variance-based) SEM. Factor-based SEM is particularly well-suited for analyzing constructs that resemble factors, while component-based SEM is designed for composites or components. Historically, in the field of tourism research, there has been a tendency to treat factor models as a statistical proxy for all types of hypothetical constructs. However, when the hypothetical construct is incorrectly modeled as a factor instead of a composite, which is its appropriate representation, it can result in bias in parameter estimates. The information presented in this study highlights that this practice has persisted even in top-tier tourism journals, including articles published in the ABAC journal. Contemporary practices that align with the current research landscape in tourism are synthesized. These practices acknowledge that hypothetical constructs can either be factors or components. To illustrate this, a hypothetical example related to cannabis tourism is used, modelling it using mixed constructs based on IGSCA-SEM. Researchers are consequently encouraged to employ SEM, particularly when aiming to publish in the ABAC journal, to enhance their methodological rigor by adopting the recommended practices outlined.

Linkages between technologies and supply chain performance: benefits, power and risk reduction

PurposeThe purpose of this paper is to assess the combined impact of the Industry 4.0 blockchain and industrial internet of things technology (IIoT) technologies on the development of supply chain linkages associated with power, benefits and risk reduction and the ultimate impact of the linkages on supply chain performance.Design/methodology/approachA structural model with blockchain and IIoT as antecedents to the supply chain power, benefits and risk reduction linkages and the linkages as antecedent to supply chain performance is theorized. Data collected from 303 US manufacturing managers are analyzed using a covariance-based structural equation modeling (CB/SEM) methodology.FindingsThe CB/SEM results indicate that blockchain technology does not directly impact implementation of the linkages. Rather, implementation of blockchain technology supports implementation of IIoT technology, which strengthens supply chain linkages, thereby improving supply chain performance.Research limitations/implicationsTo the best of the authors’ knowledge, this study is one of the first to provide empirical evidence that Industry 4.0 technologies such as blockchain and IIoT strengthen linkages among supply chain partners related to power, benefits and risk reduction and that those stronger linkages lead to improved supply chain performance. It should be noted that this study is based on data from managers representing only one sector (manufacturing) and one country (USA). Replication based on data from other sectors and countries is needed to support generalization of the results.Practical implicationsPractitioners are provided with empirical evidence that the implementation of Industry 4.0 technologies such as blockchain and IIoT support supply chain management. These technologies facilitate data and information sharing among supply chain partners, enabling the integration and coordination of business processes throughout the entire supply chain.Social implicationsThe ultimate customers of supply chains benefit when supply chain partners work together efficiently and effectively. The implementation of blockchain and IIoT digital technologies lead to improve linkages among supply chain partners driving improvements in both efficiency and effectiveness, thus benefiting customers and society.Originality/valueIndustry 4.0 technologies are relatively new with the promise of improved supply chain performance. The efficacy of Industry 4.0 technologies as mechanisms to enhance information sharing is demonstrated based on the results of this study.