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Analytics thrives in navigating emergency situations. Emergency operations management needs to develop analytics empowerment capability (ANEC) to prepare for uncertainty, support continuity and tackle any disruptions. However, there is limited knowledge on ANEC and its effects on strategic emergency service agility (SESA) and emergency service adaptation (ESAD) in such contexts. Drawing on the dynamic capability (DC) theory, we address this research gap by developing an ANEC model. We also model the effects of ANEC on SESA and ESAD using SESA as a mediator. We also assess the moderating and quadratic effects of ANEC on two higher-order DCs (i.e. SESA and ESAD).

Drawing on the literature on big data, empowerment and DC, we develop and validate an ANEC model using data from 245 service systems managers in Australia. The study uses the partial least squares-based structural equation modelling (PLS-SEM) to prove the research model. The predictive power of the research model is validated through PLSpredict (k = 10) using a training sample (n = 220) and a holdout sample (n = 25).

The findings show that analytics climate, technological enablement, information access, knowledge and skills, training and development and decision-making ability are the significant components of ANEC. The findings confirm strategic emergency service agility as a significant partial mediator between ANEC and emergency service adaptation. The findings also discuss the moderating and quadratic effects of ANEC on outcome constructs. We discuss the implications of our findings for emergency situations with limitations and future research directions.

The findings show that building ANEC plays a fundamental role in developing strategic agility and service adaptation in emergency situations to prepare for disruptions, mitigate risks and continue operations.

The ability of a business to outperform its rivals is known as its competitive edge, and it presents special difficulties in the context of the “digital revolution,” or the fourth industrial revolution. To obtain a competitive edge in the startup operations 4.0 era, this study aims to examine the organizational, technological and competence-related challenges presented by Industry 4.0. It does this by concentrating on the tools, competencies, methods, approaches, tools and strategies that are crucial. Using the Total Interpretive Structural Modeling (TISM) technique, the goal is to find, analyze and classify enablers for startup operations 4.0.

A closed-ended questionnaire and planned interviews were used in the data collection process. In startup operations 4.0, the cross-impact matrix multiplication applied to classification method is used to rank and categorize competitive advantage factors, whereas the TISM technique is used to analyze how components interact.

The study highlights the critical significance of the “Internet of Things (IoT),” “information technologies,” “technological platforms,” “employee empowerment,” “augmented reality (AR)” and “operational technologies” in its identification of 12 enablers for startup operations 4.0.

The main focus of the study is on the variables that affect startup operations 4.0’s competitive advantage.

Academics and important stakeholders can better understand the factors influencing competitive advantage in startup operations 4.0 with the help of this research.

Large businesses have been profoundly impacted by Industry 4.0 principles; however, startup operations 4.0’s competitive advantage has not received as much attention. This paper offers a fresh take on the concept of competitive advantage in startup operations 4.0 research.

Drawing on information processing view (IPV) theory, the objective of this study is to explore big data analytics (BDA) in pharmaceutical supply chain (PSC) for better business intelligence. Supply chain operations reference (SCOR) model is used to identify and discuss the likely benefits of BDA adoption in five processes: plan, source, make, deliver and return.

Semi-structured interviews with managers in a triad comprising pharmaceutical manufacturers, wholesalers/distributors and public hospital pharmacies were undertaken. NVivo software was used for thematic data analysis.

The findings revealed that BDA capability would be more practical and helpful in planning, delivery and return processes within PSC. Sourcing and making processes are perceived to be less beneficial.

The study informs managers about the strategic role of BDA capabilities in SCOR processes for improved business intelligence.

Adoption of BDA in SCOR processes within PSC is a step towards resolving the challenges of drug shortages, counterfeiting and inventory optimisation through timely decision. Despite its innumerable benefits of BDA, Australian PSC is far behind in BDA investment. The study advances the IPV theory by illustrating and strengthening the fact that data sharing and analytics can generate real-time business intelligence helping in better health care support through BDA-enabled PSC.

This study investigates the challenges and opportunities that organisations face in implementing Quality 4.0 as an approach to quality management and investigate the current state of Quality 4.0 implementation.

This study uses a qualitative research methodology to interview senior managers from globally based manufacturing and service industries.

The study explicates that most organisations implemented Quality 4.0 to improve their flexibility, efficiency, transparency and productivity while focusing on improving service quality, customer satisfaction and reducing cost. In terms of sustainability of Quality 4.0 the key factors found were a consistent effort from the top management, continuous training to employees, building leadership quality and creating a habit of using Quality 4.0.

The findings of this study offer useful guidance to organisations desirous of implementing Quality 4.0. In addition, the findings have identified key sustainability factors, helping organisations ensure a successful implementation and long-term returns from Quality 4.0.

The findings of this study contribute to the body of knowledge related to Quality 4.0 and help organisations in their digital transformation journey. In addition, it is one of the first studies to investigate the key factors for Quality 4.0 sustainability.

This case study aims to explore the efforts of a small start-up company, whose unique solutions are being deployed in the fight against COVID-19, with encouraging results. Using innovative technology and local volunteer networks, they have set out to identify the medical needs of local care providers, while reducing the effects of fraud, corruption and mis-management.

This case study involved the interrogation of data made available by the company and an interview with the chief executive officer.

The research suggests that small enterprises can have a positive impact, far beyond what either the state or the market might assume. By properly equipping and empowering people at the grassroots level, they can identify and solve local resourcing issues and root-out fraud, corruption and mismanagement before they happen.

This is a unique approach to the problem of resource management in the non-profit sector, with implications for grant projects beyond the COVID-19 pandemic.

The purpose of this paper is to take a student-centred perspective to understanding the range of ways that students respond to receiving information about their learning behaviours presented on a dashboard. It identifies four principles to inform the design of dashboards which support learner agency and empowerment, features which Prinsloo and Slade (2016) suggest are central to ethical adoption of learning analytics.

The study involved semi-structured interviews with 24 final-year undergraduates to explore the students’ response to receiving dashboards that showed the students’ achievement and other learning behaviours.

The paper identifies four principles that should be used when designing and adopting learner dashboards to support student agency and empowerment.

The study was based on a small sample of undergraduate students from the final year from one academic school. The data are based on students’ self-reporting.

The paper suggests that these four principles are guiding tenets for the design and implementation of learner dashboards in higher education. The four principles are: designs that are customisable by students; foregrounds students sense making; enables students to identify actionable insights; and dashboards are embedded into educational processes.

The paper’s originality is that it illuminates student-centred principles of learner dashboard design and adoption.

The purpose of this study is to examine privacy issues in the e-commerce context from a power-responsibility equilibrium theory (PRE) perspective.

The data was collected using an online survey (n = 335) from online shopping consumers. This study used partial least squares-structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) techniques to empirically examine the proposed relationships.

A lack of corporate privacy responsibility and regulatory protection can deprive consumers of privacy empowerment and damage consumer trust to trigger privacy concerns and subsequent defensive responses. Also, the fsQCA revealed five causal configurations to explain high consumer defensive behaviours.

This study identifies the importance of PRE theory in the privacy context. Consumer privacy concerns, privacy empowerment and trust are established as strong mediators between corporate/regulatory privacy protection efforts and consumer backlash. The application of fsQCA verified that consumer privacy behaviour can be better explained by different configurations of the same causal antecedents.

The findings highlight the importance of increasing trust and privacy empowerment as mechanisms to manage privacy concerns and consumer backlash through responsible organisational and regulatory privacy protections. The importance of balancing power and responsibility dynamics for maintaining a healthy information exchange environment is identified.

This study extends the PRE framework of privacy to include corporate privacy responsibility, privacy empowerment and trust. This is one of the first studies to explore both antecedents and outcomes of privacy empowerment. Also, the application of complexity theory and fsQCA to explain consumers’ defensive responses is novel to the literature.

This study examines the relationship between servant leadership and its dimensions on firm performance, with big data playing the role of a mediator.

Survey responses used for analysis in this study have been taken from business managers associated reputed private sector organizations in India. A conceptual model is proposed grounded to the Conservation of Resource Theory (COR). Structural equation modeling has been used to test the proposed model.

Servant leadership significantly relates to firm performance, whereby Big Data is seen to play the role of a mediator. The results also indicate that none of the dimensions of servant leadership independently affect firm performance.

The study adds to extant research by examining the mediating mechanism of Big Data in servant leadership and firm performance. It also suggests that each dimension of servant leadership gets reflected in overall servant leadership. Here it is important to note that Big Data analytics partially mediate the effectiveness of servant leadership.

Drawing on the wisdom of ancient Chinese philosopher Xunzi, this paper aims to present a novel mechanism for governing opportunism, referred to as “cultivational governance.” By examining the role of artificial intelligence (AI) resources possessed by e-commerce platforms, the authors explore how these resources contribute to mitigating seller opportunism. The central hypothesis of this study posits that two distinct types of AI resources, namely, AI technology resources and AI human resources, serve as crucial factors in curbing seller opportunism. Furthermore, the authors propose that platform digital empowerment and value cocreation act as mediating variables linking AI resources to opportunism.

Based on the resource-based view and resource orchestration theory, the authors developed a framework and tested it using survey data from sellers. This framework encompasses five key variables: e-commerce platform’s AI technology resources, AI human resources, platform digital empowerment, value cocreation and seller opportunism. Regression analysis was used for data analysis.

The empirical results validate the effectiveness of cultivational governance mechanisms, as both AI resources effectively suppress seller opportunism through digital empowerment and value cocreation. Specifically, e-commerce platforms’ AI technology resources significantly promote value cocreation and platform digital empowerment, while AI human resources primarily contribute to platform digital empowerment. Although platform digital empowerment encourages value cocreation, its direct impact on reducing seller opportunism was not supported. Notably, value cocreation negatively affects seller opportunism.

The present research mainly contributes to the marketing channel governance literature by introducing a new approach to inhibit opportunism, namely, the cultivational governance mechanism.