A human-centric perspective exploring the readiness towards smart warehousing: the case of a large retail distribution warehouse

YesThe explosive rise in technologies has revolutionised the way in which business operate, consumers buy, and the pace at which these activities take place. These advancements continue to have profound impact on business processes across the entire organisation. As such, Logistics and Supply Chain Management (LSCM) are also leveraging benefits from digitisation, allowing organisations to increase efficiency and productivity, whilst also providing greater transparency and accuracy in the movement of goods. While the warehouse is a key component within LSCM, warehousing research remains an understudied area within overall supply chain research, accounting for only a fraction of the overall research within this field. However, of the extant warehouse research, attention has largely been placed on warehouse design, performance and technology use, yet overlooking the determinants of Artificial Intelligence (AI) adoption within warehouses. Accordingly, through proposing an extension of the Technology–Organisation–Environment (TOE) framework, this research explores the barriers and opportunities of AI within the warehouse of a major retailer. The findings for this qualitative study reveal AI challenges resulting from a shortage of both skill and mind-set of operational management, while also uncovering the opportunities presented through existing IT infrastructure and pre-existing AI exposure of management

Exploring the Impact of Business Intelligence (BI) Use on Organisational Power Dynamics: A National Health Service (NHS) Case Study

The public sector, particularly healthcare organisations are under ever increasing pressure to do more with less. This coupled with the need to keep up to the constant technological changes and ever increasing abundance of information has led to many public sector organisations adopting Business Intelligence (BI) in order to leverage business value and improve decision-making. However, many organisations such as the National Health Service (NHS) continue to fail in their Information Technology (IT) related initiatives. While the rise of BI and its growing influence in organisations has attracted much academic attention, this has largely been from architectural, design and technological perspectives, whilst little is known about how BI is used by various organisational actors to reach decisions, nor much is understood regarding its resulting impact on organisational power dynamics. Thus, there remains an under researched area of discussion in the literature from the perspective of BI users. While studies report how BI can impact organisational effectiveness, facilitate data driven decision making and supposedly overcome intuitive decision making, the extent to which BI impacts and alters power dynamics between organisational actors across the organisation has received little attention. Accordingly, this research adopts a qualitative case study approach to explore power resulting from BI use within a large NHS trust by conducting 30 semi-structured interviews consisting of operational managers and BI analysts. Through taking a human-centric approach, this research uncovers how BI is altering power dynamics between organisational actors, whereby BI analysts are becoming increasingly influential as a result of their analytical skills. It was found that operational managers are becoming more reliant upon data analysts, resulting in the analysts having more and more influence. However, this research finds it is only when the analysts supplement their technical skill-set with their institutional knowledge, that they have the ability to influence and enact power within the organisational settings. The research also offers insights into the contestations and conflicts which arise from the use of BI, between operational managers and analysts as well as between in-house analysts, based in the operation setting and the centralised analysts, operating across the entire trust. Accordingly, this research empirically validates a BI Power Enactment Framework and proposes the BI Power Matrix, which may assist policy makers in identifying determining key factors which are contributory to the success or failure of technological initiatives

Exploring the Academic - Industry Collaboration in Knowledge Sharing for Supplier Selection: Digitalizing the OEM

YesIncreasing reliance on digital technologies has led to a significant shift in how businesses operate, with many now relying heavily on digital platforms for effective planning, communication, sales, marketing, supply chain, and logistics management. In this context, knowledge sharing platforms enable academic–industry collaboration in which exchange of ideas, opinions, experience, and expertise brings collective intelligence in cooperative learning ecosystem thereby expediting decision making. However, establishing long-term commitment among the partners, allocation of time and resources for sharing tacit knowledge, collaboration among partners with different strategic priorities, and real-time knowledge sharing capabilities are essential for effective and rapid learning in knowledge sharing platforms. The present article will examine these benefits and challenges in knowledge sharing and its impact on supplier selection platforms in Asian automakers. The findings of this article will be helpful for researchers and practitioners intending to explore the role of cooperation in knowledge sharing and digital transformation amid competitive environment prevalent in the automotive industry. The potential supplier database is first examined for qualifying the capability requirements put forth in this article and further prioritized using a multicriteria decision-making technique and analytic hierarchy process. The article results reveal that the manufacturer has highly prioritized firms’ financial transparency for supplier evaluation followed by the suppliers’ cost control, quality control, and manufacturing capabilities. The article has significant theoretical and practical implications for developing robust supplier evaluation criteria for automobile industry and a digital ecosystem for original equipment manufacturers in making supplier related decisions

Sustainable Food Supply Chains: Overcoming the Challenges with Digital Technologies

YesThe purpose of this paper is to offer a consolidative approach in exploring the potential contribution of digital technologies in sustainable supply chain management (SSCM) for the sustainable performance of food supply chain business, through the circular economy concepts. As a single case study, this qualitative, interpretivist research was based on one of the largest food producers in the United Kingdom. The research utilises semi-structured interviews and applies thematic analysis to offer rich insights into SSCM challenges and their relationship with the business performance, through ten in-depth interviews. Findings derived from thematic analysis of the interview transcripts suggest four main critical success factors underpinning SSCM practices and businesses performance – i.e. business continuity, waste reduction, performance measurement approach, and organisational learning, which could use the help of digital technologies to improve. This led to seven propositions to be addressed in the future research. This research offers real, practical insights into SSCM challenges, within the context of food supply chain and explores the potential of digital technologies in overcoming them. Accordingly, the primary contribution of this work is grounded in the identification of critical success factors in SSCM for Food Supply Chains (FSC). Hence, this work contributes further to the literature on SSCM, as well as circular economy, by providing a study of a business in the context of the highly pertinent and valuable food industry

Role of big data and social media analytics for business to business sustainability: A participatory web context

YesThe digital transformation is an accumulation of various digital advancements, such as the transformation of the web phenomenon. The participatory web that allows for active user engagement and gather intelligence has been widely recognised as a value add tool by organisations of all shapes and sizes to improve business productivity and efficiency. However, its ability to facilitate sustainable business-to-business (B2B) activities has lacked focus in the business and management literature to date. This qualitative research is exploratory in nature and fills this gap through findings arising from interviews of managers and by developing taxonomies that highlight the capability of participatory web over passive web to enable different firms to engage in business operations. For this purpose, two important interrelated functions of business i.e. operations and marketing have been mapped against three dimensions of sustainability. Consequently, this research demonstrates the ability of big data and social media analytics within a participatory web environment to enable B2B organisations to become profitable and remain sustainable through strategic operations and marketing related business activities. The research findings will be useful for both academics and managers who are interested in understanding and further developing the business use of participatory web tools to achieve business sustainability. Hence, this may be considered as a distinct way of attaining sustainability

Evaluating the intention to use Industry 5.0 (I5.0) drones for cleaner production in Sustainable Food Supply Chains:an emerging economy context

YesPurpose – The purpose of this study is to evaluate food supply chain stakeholders’ intention to use Industry 5.0 (I5.0) drones for cleaner production in food supply chains. Design/methodology/approach – We used a quantitative research design and collected data using an online survey administered to a sample of 264 food supply chain stakeholders in Nigeria. The partial least square structural equation model (PLS-SEM) was conducted to assess the research’s hypothesised relationships. Findings – We provide empirical evidence to support the contributions of I5.0 drones for cleaner production. Our findings showed that food supply chain stakeholders are more concerned with the use of I5.0 drones in specific operations such as reducing plant diseases which invariably enhances cleaner production. However, there is less inclination to drones adoption if the aim was pollution reduction, predicting seasonal output and addressing workers health and safety challenges. Our findings outline the need for awareness to promote the use of drones for addressing workers hazard challenges and knowledge transfer on the potentials of I5.0 in emerging economies. Originality – This is the first study to address I5.0 drones' adoption using a sustainability model. We contribute to existing literature by extending the sustainability model to identify the contributions of drones use in promoting cleaner production through addressing specific system operations. This study addresses the gap by augmenting a sustainability model, suggesting that technology adoption for sustainability is motivated by curbing challenges categorised as drivers and mediators

Data-driven subjective performance evaluation: An attentive deep neural networks model based on a call centre case

YesEvery contact centre engages in some form of Call Quality Monitoring in order to improve agent performance and customer satisfaction. Call centres have traditionally used a manual process to sort, select, and analyse a representative sample of interactions for evaluation purposes. Unfortunately, such a process is characterised by subjectivity, which in turn creates a skewed picture of agent performance. Detecting and eliminating subjectivity is the study challenge that requires empirical research to address. In this paper, we introduce an evidence-based machine learning-driven framework for the automatic detection of subjective calls. We analyse a corpus of seven hours of recorded calls from a real-estate call centre using a Deep Neural Network (DNN) for a multi-classification problem. The study draws the first baseline for subjectivity detection, achieving an accuracy of 75%, which is close to relevant speech studies in emotional recognition and performance classification. Among other findings, we conclude that in order to achieve the best performance evaluation, subjective calls should be removed from the evaluation process, or subjective scores should be deducted from the overall results

Technology as a disruptive agent: Intergenerational perspectives

YesThis study explores how British South Asian parents perceive their children’s technology consumption through their collectivist lenses and interdependent values. The findings for this qualitative study indicate that second and third generation South Asian parents acknowledge the benefits of children’s technology use; but largely perceive technology as a disruptive agent, whereby children are becoming isolated and increasingly independent within the household. The analysis aims to understand how parents view their children’s relationship with others as a result of technology consumption. Accordingly, this paper proposes an extension of the Construal of self conceptualisation and contributes a Techno-construal matrix that establishes a dyadic connection between technology consumption and cultural values. Overall, the study reveals that children display less inter-reliance and conformance typically associated with collectivist cultures, resulting from their technology use. Consequently, parents interpret their children’s shift from interdependence to more independence as a disruptive and unsettling phenomenon within the household

Role of Business Intelligence in creating more effective organisations where data analysts as decision makers are new heroes

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Business Intelligence

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