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Purpose The purpose of this paper is to algorithmically and objectively investigate the previous literature on supply chain resilience (SCR) and advance theory by synthesizing new research domains. Design/methodology/approach A two-staged analysis approach, integrating systematic literature review (SLR) with VOSviewer co-occurrence analysis, was applied to the articles published between 2003 and 2018. Findings The authors find exponential growth in the literature on SCR over the last decade; however, there is still a gap for empirical research on numerous drivers, barriers, theories, moderators, mediators and research methods intertwined in building SCR. Research limitations/implications The review identifies major clusters in which SCR research is conducted and devises a future research agenda based on the findings of co-occurrence analysis. Practical implications The findings provide managers with a broad spectrum of factors that are indispensable to build resilience and inform business policy. Originality/value While some SLRs exist in the current literature of SCR, the authors undertake a unique analytical perspective, resulting in an idiosyncratic set of research domains for further investigation in the area.

Purpose Most of the extant literature on resilience builds on normative, conceptual or silo approaches, thereby lacking an integrative approach to cold chain logistics risks (CCLRs) and resilience. The purpose of this paper is to bridge the current research gap by developing a model, based on broad empirical evidence, of the interplay between CCLRs, resilience and firm performance (FP) in perishable product supply chains (PPSCs). Design/methodology/approach A mixed method approach is used with qualitative data from interviews and quantitative data from a survey across the supply chain. The analysis is framed by contingency theory and resource-based theory. Findings Four significant sources of CCLRs and six resources used to build resilience are identified. Then, supply chain resilience (SCR) as a moderator of the negative relationship between CCLRs and FP is corroborated. Practical implications The findings will help improve managerial understandings of critical sources of risks in cold chain logistics and resources indispensable to build resilience. The scope of the research is cold chain logistics for PPSCs, which has relevance to other cold supply chains as well. Originality/value While some theoretical frameworks suggest resilience being a moderator in the negative relationship between cold chain risks and a firm’s performance, this study empirically tests this relationship using the survey across the entire supply chain. A new empirically and theoretically driven definition of SCR is also developed.

The restructuring of global value/supply chains gained increasing attention as the unprecedented COVID-19 echoed around the world. Yet, the COVID-19 related theory-driven, large scale quantitative, and empirical studies are relatively scarce. This study advances the extant literature by empirically investigating how do firms in the global food value chains (GFVCs) re-imagine their businesses structure in response to the COVID-19-becoming more resilient and competitive to the current pandemic and similar future events. We leverage a unique data of 231 senior managers of the Australian GFVCs and examine their firms' response strategies. Drawing upon key insights from the dynamic capability view, we find that GFVCs' competitiveness is achieved when exposure to COVID-19 shocks elicits dynamic capabilities-readiness, response, recovery-and these capabilities work jointly and sequentially to cultivate resilience. A key finding of this study is that firms with domestic plus global value chain partners are more resilient than those having only global business partners. This finding implies that excessive reliance on offshoring sometimes becomes lethal, especially amid unexpected and prolonged global shocks and, therefore, companies should strike a balance between domestic and global business partners to remain competitive. These findings offer important contributions to theory, practice, and UN sustainable development goals.

PurposeThis paper aims to specifically focus on the challenges that human resource management (HRM) leaders and departments in contemporary organisations face due to close interaction between artificial intelligence (AI) (primarily robots) and human workers especially at the team level. It further discusses important potential strategies, which can be useful to overcome these challenges based on a conceptual review of extant research.Design/methodology/approachThe current paper undertakes a conceptual work where multiple streams of literature are integrated to present a rather holistic yet critical overview of the relationship between AI (particularly robots) and HRM in contemporary organisations.FindingsWe highlight that interaction and collaboration between human workers and robots is visible in a range of industries and organisational functions, where both are working as team members. This gives rise to unique challenges for HRM function in contemporary organisations where they need to address workers' fear of working with AI, especially in relation to future job loss and difficult dynamics associated with building trust between human workers and AI-enabled robots as team members. Along with these, human workers' task fulfilment expectations with their AI-enabled robot colleagues need to be carefully communicated and managed by HRM staff to maintain the collaborative spirit, as well as future performance evaluations of employees. The authors found that organisational support mechanisms such as facilitating environment, training opportunities and ensuring a viable technological competence level before organising human workers in teams with robots are important. Finally, we found that one of the toughest challenges for HRM relates to performance evaluation in teams where both humans and AI (including robots) work side by side. We referred to the lack of existing frameworks to guide HRM managers in this concern and stressed the possibility of taking insights from the computer gaming literature, where performance evaluation models have been developed to analyse humans and AI interactions while keeping the context and limitations of both in view.Originality/valueOur paper is one of the few studies that go beyond a rather general or functional analysis of AI in the HRM context. It specifically focusses on the teamwork dimension, where human workers and AI-powered machines (robots) work together and offer insights and suggestions for such teams' smooth functioning.

PurposeDespite considerable growth in literature on Industry 4.0 technologies, the research on the factors influencing the investment on these technologies in pursuit of supply chain 4.0 is yet incipient. The study aims to fill this knowledge void by exploring the perceived drivers and barriers intertwined in the implementation of supply chain 4.0 in the context of food and beverage industry.Design/methodology/approachQualitative exploratory research was employed involving 20 semi-structured interviews with senior managers from the Australian food and beverage supply chain. The interviews' data were analysed with VOSViewer software version 1.6.14.FindingsThe results unravel that reduction in supply-demand misalignment, fast-changing consumer's needs, threat of legal penalties and cost optimisation are the key drivers; whereas lack of collaboration, organisational inertia and lack of awareness are the critical barriers to implement supply chain 4.0.Research limitations/implicationsThe study derives seven propositions and a theoretical framework that need to be empirically corroborated.Practical implicationsUnderstanding of drivers and barriers will help practitioners to make more informed decision in implementation of supply chain 4.0.Social implicationsImplementation of supply chain 4.0 can enhance the performance of the food and beverage industry, thus offering more job opportunities and sustained food supply.Originality/valueThis is the first study in exploring drivers and barriers to the implementation of supply chain 4.0; thus, adds new knowledge to the growing body of the literature. The paper introduces a novel method for qualitative data analysis contributing to the methodological development of the supply chain management field.

Background: Antibiotic resistance is a global threat. Scarce knowledge about safe and appropriate antibiotic use is coupled with frequent self-administration, e.g., in China. This repeated self-medication poses potential risk in terms of antibiotic resistance. Low-resource countries are facing an elevated burden of antibiotic self-medication as compared to developed ones. Thus, this study focused on evaluating the pervasiveness of antibiotic self-medication in 3 universities of Southern Punjab, Pakistan. Methods: We conducted a descriptive cross-sectional survey in three government sector universities of Southern Punjab, Pakistan. The study was carried out with self-administered paper-based questionnaires. Data was analyzed using SPSS version 18.0 (IBM, Chicago, IL, USA). Results: Seven hundred twenty-seven students out of 750 (response rate 97%) with a mean age ± SD of 23.0 ± 3.4 years agreed to participate in the study. The proportion of females was slightly greater (52%) compared with males (48%), and almost one-third of the respondents (36%) were in their 2nd year of university. Out of the total, 58.3% practiced self-medication in the preceding six months, and 326 (45%) confirmed the use of antibiotics. Metronidazole was the most frequently self-medicated antibiotic (48%). Out of the total, 72% demonstrated awareness regarding the side effects of antibiotics. Diarrhea was the well-known adverse effect (38%). Forty-three percent affirmed having antibiotic resistance knowledge, and 30% knew that the irregular use of antibiotics would lead to increased antibiotic resistance. Conclusion: Despite having ample awareness of the adverse antibiotic reactions, self-medication among the university students was high and antibiotic resistance was a fairly unknown term.

Purpose Despite several contributions to greenhouse gas emission and carbon footprint reduction, the literature lacks empirical insights into the business impact of climate risks, when they materialize, and techniques to manage them. This study aims to devise a model delving into critical climate risks and the role of consortia and social capital to mitigate these risks. Design/methodology/approach A mixed-methods approach was used, including qualitative and quantitative data from small- and medium-sized enterprises (SMEs) in an Australian agrifood supply chain (AFSC). Findings The qualitative analysis uncovers four critical climate risks and a repertoire of relational, structural, and cognitive social capital accrued by SMEs of AFSC through consortia. The quantitative analysis corroborates that the SMEs that accumulate higher social capital through active engagement within consortia are able to respond more effectively to climate risks than to others. The authors, therefore, find that climate risk mitigation in SMEs is the function of both association (consortia) membership and the accrual of higher social capital through active involvement and collaboration within networks. Originality/value This is the first study in using a moderated-moderation model that simultaneously investigates the business impact of climate risks and how the moderating impact of consortia (a primary moderator) is further moderated by social capital (a secondary moderator) in explaining SMEs performance. The paper addresses the lack of adequate empirical research, particularly mixed-methods, in supply chain risk management literature.