The impact of Big Data analytics and data security practices on service supply chain performance

Unlocking sustainable supply chain performance through dynamic data analytics: a multiple mediation model of sustainable innovation and supply chain resilience

This article provides a theoretical framework for comprehending the connections between dynamic data analytics capability (DDAC), innovation capabilities (IC), supply chain resilience (RES), and sustainable supply chain performance (SSCP). Since this is the first empirical investigation of the sequential mediation effect between DDAC and SSCP through IC and RES, it fills a critical need in the supply chain literature. A quantitative methodology was used, involving a survey questionnaire distributed to 259 large Pakistani manufacturing firms. We used PLS-SEM to test for the expected associations. Findings show that using DDAC has a beneficial effect on both innovative and resilient capabilities, which in turn leads to better SSCP. The research illuminates the sequential mediating roles of product, process, and resilience, underlining the need of combining data-driven innovation with resilience in order to achieve sustainable supply chain performance. These results provide useful guidance for businesses that want to boost their sustainability results by taking a more all-encompassing approach to data-driven innovation and resilience.

The role of blockchain-enabled supply chain applications in improving supply chain performance: the case of Jordanian manufacturing sector

Purpose

Blockchain technology has the potential to enhance information and knowledge management among members of the supply chain. This study aims to demonstrate the direct and indirect impact of blockchain adoption on achieving supply chain competitive advantage and improving innovation capabilities to achieve greater supply chain performance.

Design/methodology/approach

The study opted for a quantitative research approach. A structured questionnaire was used to collect data from 284 respondents from various Jordanian manufacturing firms. Smart PLS software was used to conduct structural equation modelling to test the proposed hypotheses.

Findings

The analysis revealed that investing in and using blockchain-enabled supply chain applications improves the ability to achieve higher levels of productivity, lead times, customer service and relationships with supply chain members. Moreover, blockchain technology integration with supply chain management processes has a positive impact on innovative activities that support supply chain operations. Finally, blockchain adoption has enhanced supply chain performance by reducing transaction costs, improving customer service and increasing the speed of supply chain operations.

Research limitations/implications

The study provides guidance for decision-makers and academicians on the use of blockchain adoption to improve supply chain performance. Future studies should use a larger sample size and random sampling techniques to achieve better generalizability of the results.

Originality/value

The study fulfils an identified gap in the application of blockchain technology to improving supply chain performance within a broader context that encompasses supply chain innovation capabilities and competitive advantage.

Data-based drivers of big data analytics utilization: moderating role of IT proactive climate

Purpose

This study uses the resource-based view (RBV) and isomorphism to investigate the influence of data-based resources (i.e. bigness of data, data accessibility (DA) and data completeness (DC)) on big data analytics (BDA) use under the moderation effect of organizational culture (i.e. IT proactive climate). It also analyzes the possible relationship between BDA implementation and value creation.

Design/methodology/approach

The empirical validation of the research model was performed through a cross-sectional procedure to gather survey-based responses. The data obtained from a sample of 190 IT executives having relevant educational backgrounds and experienced in the field of big data and business analytics were analyzed using structural equation modeling.

Findings

BDA usage can generate significant value if supported by proper levels of DA and DC, which are benefits obtained from the bigness of data (high volume, variety and velocity of data). In addition, data-driven benefits have stronger impacts on BDA usage in firms with higher levels of IT proactive climate.

Originality/value

The present paper has extended the existing literature as it demonstrates facilitating characteristic of data-based resources (i.e. DA and DC) on BDA implementation which can be intensified with an established IT proactive climate in the firm. Additionally, it provides further theoretical and practical insights which are illustrated ahead.

When to choose ranked area integrals versus integrated gradient for explainable artificial intelligence – a comparison of algorithms

Purpose

Explainable artificial intelligence (XAI) has importance in several industrial applications. The study aims to provide a comparison of two important methods used for explainable AI algorithms.

Design/methodology/approach

In this study multiple criteria has been used to compare between explainable Ranked Area Integrals (xRAI) and integrated gradient (IG) methods for the explainability of AI algorithms, based on a multimethod phase-wise analysis research design.

Findings

The theoretical part includes the comparison of frameworks of two methods. In contrast, the methods have been compared across five dimensions like functional, operational, usability, safety and validation, from a practical point of view.

Research limitations/implications

A comparison has been made by combining criteria from theoretical and practical points of view, which demonstrates tradeoffs in terms of choices for the user.

Originality/value

Our results show that the xRAI method performs better from a theoretical point of view. However, the IG method shows a good result with both model accuracy and prediction quality.

Big data analytics capability and supply chain performance: the mediating roles of supply chain resilience and innovation

Purpose

Big data analytics (BDA) capabilities can affect supply chain performance in several ways. The main purpose of this study was to understand how BDA capabilities could affect supply chain performance through supply chain resilience and supply chain innovation.

Design/methodology/approach

The study adopted a cross-sectional approach to collect survey-based responses to examine the hypotheses. Accordingly, 187 responses were collected and analyzed using partial least squares (PLS) in the SmartPLS3.

Findings

The results showed that BDA capabilities improve supply chain performance through resilience and innovation of the supply chain.

Originality/value

The present study also contributed to the existing literature by demonstrating the mediating role of supply chain resilience and supply chain innovation between BDA capabilities and supply chain performance. In this context, some theoretical and managerial implications were proposed and discussed.

Big Data Analytics in Supply Chain Management: A Systematic Literature Review and Research Directions

Big data analytics has been successfully used for various business functions, such as accounting, marketing, supply chain, and operations. Currently, along with the recent development in machine learning and computing infrastructure, big data analytics in the supply chain are surging in importance. In light of the great interest and evolving nature of big data analytics in supply chains, this study conducts a systematic review of existing studies in big data analytics. This study presents a framework of a systematic literature review from interdisciplinary perspectives. From the organizational perspective, this study examines the theoretical foundations and research models that explain the sustainability and performances achieved through the use of big data analytics. Then, from the technical perspective, this study analyzes types of big data analytics, techniques, algorithms, and features developed for enhanced supply chain functions. Finally, this study identifies the research gap and suggests future research directions.

The impact of business intelligence on supply chain performance with emphasis on integration and agility–a mixed research approach

Purpose

The paper aims to explore how business intelligence (BI), integration and agility influence supply chain performance.

Design/methodology/approach

The study was performed by the exploratory sequential mixed method in two phases including meta-synthesis as a qualitative method and survey as a quantitative method. Data were collected through a survey of 369 Iranian companies across various industries. Structural equation modeling was used to test hypotheses.

Findings

The results show that BI, integration and agility play an important role in achieving better supply chain performance. In the meantime, BI has the greatest impact on supply chain performance. Additionally, BI has a positive and significant effect on the integration and agility of the supply chain. The study also found that integration has a direct effect on supply chain agility.

Originality/value

To the best of the authors' knowledge, the paper theoretically and empirically presents a new conceptual model of the relationship between BI, integration, agility and supply chain performance. The study helps researchers and practitioners to achieve insights into supply chain performance improvement.

Using blockchain technology to drive operational excellence in perishable food supply chains during outbreaks

Purpose

This paper aims to explore the potential of blockchain technology (BT) to support the operational excellence in perishable food supply chain (PFSC) during outbreaks, by doing use-case analysis.

Design/methodology/approach

A systematic literature review is performed to determine the dimensions of operational excellence in the food supply chain (FSC), then a single use-case analysis is conducted to explore the potential of blockchain in order to achieve operational excellence for PFSC during the pandemics by applying context, interventions, mechanism and outcomes (CIMO) logic.

Findings

The findings of this study reveal that blockchain capabilities such as immutability and transparency, visibility, traceability, integration and interoperability, disintermediation and decentralisation, smart contracts and consensus mechanism provide better sustainable operational excellence outcomes for PFSCs to be more responsive, flexible, efficient and collaborative to cope with the impacts of COVID-19.

Research limitations/implications

This research employs only one real case with multiple PFSC participants. Statistical generalisation is not possible at this stage of the research. However, the findings are not restricted to this single use-case.

Practical implications

This study provides a research direction to explore the potential of BT to achieve operational excellence in the PFSC during outbreaks and generates prescriptive knowledge for better managerial decision-making across the PFSC during outbreaks.

Originality/value

This research conducts semi-structured interviews with different participants in one blockchain ecosystem to understand multiple participants' perspectives of operational excellence within PFSC.

S. Impact of AI regulation and governance on online personal data sharing: from sociolegal, technology and policy perspective

Purpose

The purpose of this study is to investigate the impacts of regulations and governance of artificial intelligence (AI) on personal data sharing (PDS) in the context of sociolegal, technology and policy perspective.

Design/methodology/approach

With the help of theories and literature review, some hypotheses have been formulated and a conceptual model has been developed. These are statistically validated. The validated model has been compared again using impact of regulation and governance of AI as a moderator. The validation has been done using survey by PLS analysis.

Findings

The study found that there is a high level of positive impact of regulation and governance of AI on the online PDS by the users.

Research limitations/implications

This study has provided a statistical model which can provide the antecedents of PDS by the online users with the impact of AI regulation and governance as a moderator. The proposed model has explanative power of 92%.

Practical implications

The study highlighted that there is a necessity of having appropriate AI regulations so that users could share their personal data online without any hesitation. Policymakers and legal fraternity should work together to formulate a comprehensive AI regulation and governance framework.

Originality/value

To the best of the authors’ knowledge, there is no study on the impact of AI regulation and governance towards PDS and how it impacts on the security, privacy and trust of the online users.

The role of big data analytics capabilities in bolstering supply chain resilience and firm performance: a dynamic capability view

Purpose

Big data analytics capability (BDAC) can affect firm performance in several ways. The purpose of this paper is to understand how BDA capabilities affect firm performance through supply chain resilience in the presence of the risk management culture.

Design/methodology/approach

The study adopted a cross-sectional approach to collect survey-based responses to examine the hypotheses. 167 responses were collected and analyzed using partial least squares in SmartPLS3. The respondents were generally senior IT executives with education and experience in data and business analytics.

Findings

The results show that BDA capabilities increase supply chain resilience as a mediator by enhancing innovative capabilities and information quality, ultimately leading to improved firm performance. In addition, the relationship between supply chain resilience and firm performance is influenced by risk management culture as a moderator.

Originality/value

The present study contributes to the relevant literature by demonstrating the mediating role of supply chain resilience between the BDA capabilities relationship and firm performance. In this context, some theoretical and managerial implications are proposed and discussed.

The nexus of information sharing, technology capability and inventory efficiency

Purpose

This paper aims to examine the effect of inventory information sharing on inventory efficiency and its intervening effect of information technology (IT) capability in manufacturing firms.

Design/methodology/approach

Stratified random sampling and filter questions selected targeted respondents, and an online survey collected 124 completed questionnaires from Malaysian manufacturing firms. partial least squares structural equation modeling (PLS-SEM) examined the structural model and hypothesis statement. An analysis of importance-performance map analysis (IPMA) test identified the relative importance drivers of inventory efficiency.

Findings

The findings showed that enhanced IT capabilities in manufacturing firms mediate a positive relationship between inventory sharing and inventory efficiency.

Research limitations/implications

This study portrays the relationship between inventory level, demand and information sharing. The research was carried out only within Malaysian manufacturing firms.

Practical implications

These findings will enable the management of manufacturing firms to design and visualise their inventory levels and share best practices across supply chain networks to achieve effective and optimised inventory planning.

Social implications

This study illustrates an intervention model that offers a direct and indirect impact of IT capabilities that allow scholars to close inventories productivity gaps in research.

Originality/value

This paper extends the limited literature on the sharing of inventory information and inventory productivity, notably from a strategic management perspective. The findings help scholars clearly understand the information systems capability and its mediating impact on information sharing and inventory efficiency’s relationship in the manufacturing sector. Moreover, demand information sharing affected the dynamic supply chain.

Measuring the maturity of service supply chain process: a new framework

Purpose

The aim of this study is to develop a framework for measuring of service supply chain (SSC) maturity process.

Design/methodology/approach

The main framework of the SSC maturity was developed by reviewing the concepts and models of SSC, business excellence, maturity and supply chain performance evaluation. Then, the maturity level of each excellence criterion was defined in the proposed model by using the excellence criteria for SSC and the concept of Plan, Do, Check and Act (PDCA) cycle in combination with the process survey tools maturity model. Based on the excellence criteria and their maturity levels, a questionnaire was designed to practically measure the proposed framework.

Findings

The concepts and features of maturity levels defined for each of the excellence criteria were used to implement and operationalize the proposed framework and evaluate the SSC processes.

Practical implications

Through the assessment of the existing status of SSC processes, the findings allow managers to reach a better understanding of the strengths and weaknesses of such processes. Then, some opportunities are provided for improving each excellence criterion to enhance the performance of each process.

Originality/value

In fact, this study provides guidelines for organizations to measure their progress and performance and improve their management systems. The main advantages of the proposed SSC measurement framework include self-assessment facilitation, calculation of criteria scores and development of uses. The proposed model, like quality and productivity awards, can pave the way for increased competitiveness of the service industry.

Service supply chain: from bibliometric analysis to content analysis, current research trends and future research directions

Purpose

The purpose of this study is to carry out the systematic literature review, bibliometric analysis and content analysis of extant literature of service supply chain (SSC).

Design/methodology/approach

Systematic literature review (SLR) technique was used for identifying the research papers. In the first step after reading titles, abstracts and keywords and, full-length articles wherever required, papers not related to SSC were removed. In second steps papers were read more critically and papers not related to SSC were removed. Finally on 502 papers bibliometric and content analysis was further carried out. Content analysis was based on the clusters formed by bibliographic coupling. Further, content analysis of the recent articles revealed the current research trends and research gaps.

Findings

This paper identified the six existing research diversifications in SSC as (1) logistics SSC, (2) model, framework and conceptual papers, (3) third-party logistics service providers, (4) articles from various perspective, (5) measurement of quality and performance on services and (6) impact of adoption of technology, cooperation and branding on logistics service providers. Further, six future research directions are also provided.

Practical implications

This research provides a clear view of the progression of publication, research diversification, research themes of six identified clusters, sub-themes of clusters and content analysis of each cluster. Content analysis of recent articles reveals the current research trend and future research directions.

Originality/value

This is a first of its kind of study which presents the diversification of research areas within SSC, bibliometric analysis, content analysis and provides actionable future research direction.

Supply chain management 4.0: a literature review and research framework

Purpose

This article presents a review of the existing state-of-the-art literature concerning Supply Chain Management 4.0 (SCM 4.0) and identifies and evaluates the relationship between digital technologies and Supply Chain Management.

Design/methodology/approach

A literature review of state-of-the-art publications in the subject field and a bibliometric analysis were conducted.

Findings

The paper identifies the impact of novel technologies on the different supply chain processes. Furthermore, the paper develops a roadmap framework for future research and practice.

Practical implications

The proposed work is useful for both academics and practitioners as it outlines the pillar components for every supply chain transformation. It also proposes a range of research questions that can be used as a base to guide the future research direction of the field.

Originality/value

This paper presents a novel and original literature review-based study on SCM4.0 as no comprehensive review is available where bibliometric analysis, motivations, barriers and technologies' impact on different SC processes have been considered.

Exploring the consequences of judgmental and quantitative forecasting on firms' competitive performance in supply chains

Purpose

The purpose of this study is to examine the impacts of different forecasting methods (judgmental, quantitative and mixed forecasting) on firms' supply chains and competitive performance.

Design/methodology/approach

Working with three groups of manufacturing companies, we explore the consequences of judgmental, quantitative and mixed forecasting methods on firms' competitive performance in supply chains. The validity of constructs and path relationships was examined using structural equation modeling (SEM).

Findings

Our findings indicate that supply chain efficiency influences both cost reduction and customer satisfaction. In addition, the three dimensions of supply chain performance are shown to be direct antecedents of competitive performance. Our empirical results reveal that although all studied forecasting methods meaningfully influence supply chain performance, the mixed method, compared to the other two methods, has greater capabilities to enhance supply chain performance.

Originality/value

This research provides originality and insight into supply chain practices through forecasting methods to improve competitive performance.

The nexus between supply chain analytic, innovation and robustness capability

Purpose

By drawing on knowledge-based view, this paper aims to test causal model linking supply chain analytics, innovation, robustness capability and firm age. More specifically, the mediating role of supply chain innovation on supply chain analytics and robustness capability link and the moderating role of firm age.

Design/methodology/approach

Survey data were procured from companies operating in the United Arab Emirates using a simple random sampling technique. The obtained data were analyzed with variance-based structural equation modeling (PLS-SEM).

Findings

The findings from PLS-SEM revealed that supply chain innovation fully mediate supply chain analytics and robustness capability associations. Findings from multi-group analysis (MGA) denote that firm age did not moderate any of the paths of the research model. Suggesting that the associations are similar for old, mid-aged and younger firms.

Originality/value

This work demonstrates that supply chain analytic is valuable tool that can foster innovation and robustness in supply chain. This work is among the first to scrutinize the variation among old, mid-aged and younger firms in supply chain analytics research stream. The paper concludes with implications for theory and practice.

Promoting a revamped CRM through Internet of Things and Big Data: an AHP-based evaluation

Purpose

Internet of things (IoT) and big data (BD) could change how the societies function. This paper explores the role of IoT and BD and their impact on customer relationship management (CRM) investments in modern customer service. The purpose of this paper is to develop an analytic hierarchy planning framework to establish criteria weights and to develop a general self-assessment model for determining the most important factors influencing the IoT and BD investment in CRM. The authors found that most studies have focused on conceptualizing the impact of IoT without BD and with limited empirical studies and analytical models. This paper sheds further light on the topic by presenting both IoT and BD aspects of future CRM.

Design/methodology/approach

The analytic hierarchy process (AHP) methodology is used to weight and prioritize the factors influencing the IoT and BD investment in modern CRM in the service industry. The AHP framework resulted in a ranking of 21 sustainability sub-factors based on evaluations by experienced information technology and customer service professionals.

Findings

The paper provides significant insight on the new frontier of CRM, focusing on the use of IoT and BD and the respective solutions to address them were identified. This study primarily contributes in providing the process of effectively managing and implementing IoT and BD in big businesses by identifying the connecting link between firms and customers.

Practical implications

The understanding of new frontier of CRM connective via IoT and BD can solve the dilemmas and challenges linked to the practice of implement IoT and BD in the information systems field. The study provides valuable information and critical analysis of IoT and BD with regard to the integration of CRM. Finally, this study further provides directions for future researchers.

Originality/value

IoT and BD are a growing phenomenon, which business decision-makers and information professionals need to consider seriously to properly ascertain the modern CRM dimensions in the digital economies. They also should embrace the proper CRM innovation, which is powered by IoT and BD, and discover how IoT and BD can bring the next level of maturity to CRM “CRM of everything.”

Building supply chain risk resilience

Purpose

The purpose of this paper is to examine how firms can develop business risk resilience from supply chain disruption events, by developing big data analytics (BDA) capabilities within their organization. The authors test whether BDA mediates the impact of institutional response to supply chain disruption events, and information technology infrastructure capabilities (ITICs), on firm’s ability to develop risk resilience from supply chain disruption events.

Design/methodology/approach

The study is based on survey data collected from 225 firms, spread across several sectors in the USA and Europe. The respondents are primarily senior and middle management professionals who have experience within the information technology (IT) and supply chain domain. Validity and reliability analyses were performed using SPSS and AMOS; and covariance-based structural equation modeling was used to test the hypothesis.

Findings

The analysis reveals two significant findings. First, the authors observe that institutional experience with managing supply chain disruption events has a negative impact on firm’s ability to develop business risk resilience. However, if the organizations adopt BDA capabilities, it enables them to effectively utilize resident firm knowledge and develop supply chain risk resilience capacity. The results further suggest that BDA positively adds to an organization’s existing IT capabilities. The analysis shows that BDA mediates the impact of ITIC on the organization’s ability to develop risk resilience to supply chain disruption events.

Originality/value

This study is one of the few works that empirically validate the important role that BDA capabilities play in enabling firms develop business risk resilience from supply chain disruption events. The study further provides a counterpoint to the existing perspective within the supply chain risk management literature that institutional experience of managing past supply chain disruption events prepares the organization to deal with future disruption events. This paper adds to our understanding of how, by adopting BDA capabilities, firms can develop supply chain risk resilience from disruption events.

Service supply chain management: a behavioural operations perspective

Purpose

The purpose of this paper is to provide an overview of the evolution of service supply chain management from a behavioural operations perspective, pointing out future research directions for scholars.

Design/methodology/approach

This study searched five databases for relevant literature published between 2009 and 2018, selecting 64 papers for this review. The selected literature was categorised according to two dimensions: a service supply chain link perspective and a behavioural factor perspective. Comparative analysis was used to identify gaps in the literature, and five future research agendas were proposed.

Findings

In terms of the perspective of service supply chain link, extant literature primarily focuses on service supply and service co-ordination management, and less on service demand and integration management. In terms of the behavioural factor’s perspective, most focus on classic behaviour factors, with less attention paid to emerging behaviour factors. This paper thus proposes five research agendas: demand-oriented management and integrated supply chain-oriented behavioural research; broadening the understanding of the scope of behavioural operations; integrating the latest backgrounds and trends of service industry into the research; greater attention to behavioural operations in service sub-industries; and multimethod combination is encouraged to be used to dig into the interesting research problems.

Originality/value

This study constitutes the first systematic review of service supply chain research from a behavioural perspective. By categorising the literature into two dimensions, the state of existing research is evaluated with an eye towards future research avenues.