Implementing mixed methods research in supply chain management

Identifying Application Areas for Machine Learning in the Retail Sector: A Literature Review and Interview Study

Machine learning (ML) has the potential to take on a variety of routine and non-routine tasks in brick-and-mortar retail and e-commerce. Many tasks previously executed manually are amenable to computerization using ML. Although procedure models for the introduction of ML across industries exist, the tasks for which ML can be implemented in retail need to be determined. To identify these application areas, we followed a dual approach. First, we conducted a structured literature review of 225 research papers to identify possible ML application areas in retail, as well as develop the structure of a well-established information systems architecture. Second, we triangulated these preliminary application areas with the analysis of eight expert interviews. In total, we identified 21 application areas for ML in online and offline retail; these application areas mainly address decision-oriented and economic-operative tasks. We organized the application areas in a framework for practitioners and researchers to determine appropriate ML use in retail. As our interviewees provided information at the process level, we also explored the application of ML in two exemplary retail processes. Our analysis further reveals that, while ML applications in offline retail focus on the retail articles, in e-commerce the customer is central to the application areas of ML.

Is it alright to use artificial intelligence in digital health? A systematic literature review on ethical considerations

The application of artificial intelligence (AI) not only yields in advantages for healthcare but raises several ethical questions. Extant research on ethical considerations of AI in digital health is quite sparse and a holistic overview is lacking. A systematic literature review searching across 853 peer-reviewed journals and conferences yielded in 50 relevant articles categorized in five major ethical principles: beneficence, non-maleficence, autonomy, justice, and explicability. The ethical landscape of AI in digital health is portrayed including a snapshot guiding future development. The status quo highlights potential areas with little empirical but required research. Less explored areas with remaining ethical questions are validated and guide scholars' efforts by outlining an overview of addressed ethical principles and intensity of studies including correlations. Practitioners understand novel questions AI raises eventually leading to properly regulated implementations and further comprehend that society is on its way from supporting technologies to autonomous decision-making systems.

Leadership styles in supply chain disruptions: a multimethod evaluation based on practitioner insights

Purpose

The authors empirically determine the stages and leadership styles that enhance the effectiveness of firm response and recovery efforts during each stage.

Design/methodology/approach

The authors use an inductive exploratory approach and mixed-method research design. Study 1 uses a combination of qualitative data gathered through two rounds of exploratory focus groups (26 managers and executives), Q-sorting (60 participants) and a confirmatory focus group (6 experts) to highlight how expert practitioners perceive the staged progression of a supply chain disruption. Study 2 uses responses from 90 experienced managers in an experimental vignette to determine the most effective leadership style during each stage.

Findings

Expert practitioners are strongly partial to a two-staged disruption model that includes an early/response and late/recovery stage. They consider decisiveness to be the most effective style in the response stage. However, in the recovery stage, a style that combines decisiveness and task-centered leadership is perceived to be the most effective. Further, effective leadership hinges on applying distinct styles depending on the progression of events during supply chain disruptions.

Originality/value

Empirical evidence and validation of conceptual models on leadership behavior during crises are essentially nonexistent in the literature. This study is likely the first to pursue the subject of leadership during stages of crises and the first to offer empirical evidence thereof. Relatedly, the authors contribute to the growing research on crisis management, which is likely to receive even more attention as the frequency and size of crises facing organizations increase.

Manufacturing and service supply chain resilience to the COVID-19 outbreak: Lessons learned from the automobile and airline industries

There has been an increased interest among scholars to investigate supply chain resilience (SCRes) in manufacturing and service operations during emerging situations. Grounded in the SCRes theory, this study provides insights into the impact of the COVID-19 outbreak on the automobile and airline supply chain. Both the short and long-term response strategies adopted by the two supply chains are assessed, using a combination of qualitative and quantitative techniques in three distinct phases. In phase one, we use a sequential mixed-method for resilience evaluation, integrating Time-to-Recovery (TTR) and Financial Impact (FI) analysis. In phase two, we conduct an empirical survey involving 145 firms to evaluate the short-term SCRes response strategies. In the third phase, we conduct semi-structured interviews with supply chain executives both from the automobile and airline industries to understand the long-term SCRes response strategies. Our findings indicate that: (i) the automobile industry perceived that the best strategies to mitigate risks related to COVID-19, were to develop localized supply sources and use advanced industry 4.0 (I4.0) technologies. (ii) The airline industry on the other hand, perceived that the immediate need was to get ready for business continuity challenges posed by COVID-19, by defining their operations both at the airports and within the flights. (iii) Importantly, both the sectors perceived Big Data Analytics (BDA) to play a significant role by providing real-time information on various supply chain activities to overcome the challenges posed by COVID-19. (iv) Cooperation among supply chain stakeholders is perceived, as needed to overcome the challenges of the pandemic, and to accelerate the use of digital technologies.

A step-by-step guide to assist logistics managers in defining efficient re-shelving solutions for retail store deliveries

Purpose

City logistics is a challenge in many cities. Literature works focus on the analysis of large or local-scale solutions to increase the efficiency of freight transport. However, store deliveries from the perspective of practitioners, particularly retail stores, are still an issue. In this context, the purpose of this paper is to propose a decision framework to assist logistics managers in defining efficient re-shelving solutions for store deliveries, according to the emplacement characteristics, city administration constraints and social issues.

Design/methodology/approach

An iterative step-by-step decision framework is developed, which allows taking decisions in a clear and structured way, including the preferences of key stakeholders. Moreover, a “what if” procedure is proposed, aiming to modify some initial conditions of the target store to achieve more efficient solutions.

Findings

The proposed decision framework is applicable in practice and helps users (mainly logistics managers) to identify solutions for efficient re-shelving in urban settings.

Research limitations/implications

The decision framework is applied by the logistics manager of two Spanish food retail stores, but it could be used in different logistics sectors and cities/regions, although adapting the decisions taken at each phase.

Practical implications

Logistics managers have a support tool when addressing re-shelving solutions for store deliveries.

Social implications

A balance can be found between company interests (minimise costs) and citizens quality of life (less contamination, noise, traffic, etc.).

Originality/value

This study simultaneously deals with large- and local-scale decisions faced by logistics managers in their day-to-day activity, considering details about the store location, its surroundings and the company it belongs.

The obstacles to cold chain implementation in developing countries: insights from Vietnam

Purpose

The purpose of this paper is to identify the obstacles that impede cold chain implementation in developing countries.

Design/methodology/approach

A grounded theory methodology was employed to execute this research. Eight semi-structured, in-depth interviews were conducted with senior managers in Vietnam. In addition, consistent with grounded theory guidelines, the authors utilized archival data to facilitate theory development.

Findings

The results of the analysis revealed a total of ten key obstacles: deficient professional skills, lack of quality and safety-control measures, high concentration of intermediaries, poor infrastructure, lack of information systems, high cost of installation and operation, inadequate education and training at farmer level, deficiency of standardization, lack of government support for local businesses and social norms.

Originality/value

Although many authors have recognized the enormity of food wastage and limited employment of cold chain in developing countries compared to developed countries, few efforts have been made to explore the reasons for the limited use of cold chains in developing countries. There are several noteworthy theoretical and managerial contributions that emerged from addressing this gap.

An exploratory study of Internet of Things (IoT) adoption intention in logistics and supply chain management

Purpose

The Internet of Things (IoT) envisions a global infrastructure of networked physical objects that render radical transparency to supply chain management. Despite the perceived advantages of IoT, industry has still not widely adopted IoT-enabled logistics and supply chain management. The purpose of this paper is to understand the incentives and concerns behind firms’ decisions to adopt IoT, explore the determinant factors affecting IoT adoption in logistics and supply chain management.

Design/methodology/approach

This study uses mixed methods research to explore the determinants of IoT adoption intention in logistics and supply chain management. Qualitative analysis using the Grounded Theory methodology reveals the underlying perceptions regarding logistic innovation with IoT. Quantitative hypotheses are then developed based on qualitative investigation and adoption literature. Survey data were collected from the managerial staff of Taiwanese firms across various industries. Structural equation modeling with partial least square is used for data analysis.

Findings

The results of the qualitative study identify uncertainties and issues regarding firms’ intention to accept or reject IoT technology in logistics and supply chain management, including the benefit and cost aspects of adopting IoT, uncertainties about the trustworthiness of IoT technology, and the external motivating force to embrace IoT. The resulting quantitative model shows that perceived benefits, perceived costs, and external pressure are significant determinants of IoT adoption intention, while technology trust is not. However, technology trust does indirectly influence IoT adoption intention through perceived benefits.

Practical implications

The empirical findings of this study provide some guidelines for logistics and supply chain managers to evaluate IoT adoption in their firms. Likewise, IoT solution providers can also benefit from this study by improving their solutions to mitigate the IoT adoption concerns addressed herein.

Originality/value

This paper is among the first known to examine IoT adoption intention in logistics and supply chain management using mixed methods research. The mixed methods approach offers a better insight in understanding incentives behind firms’ decisions to adopt IoT vs the use of either a qualitative or quantitative method alone.

Human parasitology worldwide research

In this article, the trends in human parasitology have been studied through the analysis of the number of publications in this area. The parameters studied were: number of articles, language, countries and institutions with the highest number of publications, and keywords with greater presence in the articles of human parasitology. The results of the analysis confirm the growing interest in this area, observing an exponential growth in the number of publications in the last decades. We also verified that the main country in terms of scientific production is the USA, although among the most important institutions, we find non-US centres such as the Oswaldo Cruz Foundation and the London School of Hygiene and Tropical Medicine. For observing the relative importance of the journals that publish articles in this specific topic, an index has been created based on the h-index of the journal with publications related to human parasitology and divided by every 100 items. This rank is led fist by 'Journal of Medical Entomology' closely followed by 'Parasitology'. The analysis of the keywords allows to draw conclusions about the great importance of malaria in the current world research. A change in analytical methodology is also observed, and molecular techniques are now being imposed. These techniques, in the near future, have to influence in an improvement in the treatments and prevention of the diseases caused by parasites. Finally, it can be seen that diseases traditionally studied as helminthiasis and amebiasis are currently as well studied as others such as toxoplasmosis or leishmaniasis.

A global exploration of Big Data in the supply chain

Purpose

Journals in business logistics, operations management, supply chain management, and business strategy have initiated ongoing calls for Big Data research and its impact on research and practice. Currently, no extant research has defined the concept fully. The purpose of this paper is to develop an industry grounded definition of Big Data by canvassing supply chain managers across six nations. The supply chain setting defines Big Data as inclusive of four dimensions: volume, velocity, variety, and veracity. The study further extracts multiple concepts that are important to the future of supply chain relationship strategy and performance. These outcomes provide a starting point and extend a call for theoretically grounded and paradigm-breaking research on managing business-to-business relationships in the age of Big Data.

Design/methodology/approach

A native categories qualitative method commonly employed in sociology allows each executive respondent to provide rich, specific data. This approach reduces interviewer bias while examining 27 companies across six industrialized and industrializing nations. This is the first study in supply chain management and logistics (SCMLs) to use the native category approach.

Findings

This study defines Big Data by developing four supporting dimensions that inform and ground future SCMLs research; details ten key success factors/issues; and discusses extensive opportunities for future research.

Research limitations/implications

This study provides a central grounding of the term, dimensions, and issues related to Big Data in supply chain research.

Practical implications

Supply chain managers are provided with a peer-specific definition and unified dimensions of Big Data. The authors detail key success factors for strategic consideration. Finally, this study notes differences in relational priorities concerning these success factors across different markets, and points to future complexity in managing supply chain and logistics relationships.

Originality/value

There is currently no central grounding of the term, dimensions, and issues related to Big Data in supply chain research. For the first time, the authors address subjects related to how supply chain partners employ Big Data across the supply chain, uncover Big Data’s potential to influence supply chain performance, and detail the obstacles to developing Big Data’s potential. In addition, the study introduces the native category qualitative interview approach to SCMLs researchers.

Green supply chain management practice adoption in Ugandan SME manufacturing firms

Purpose

– The purpose of this paper is to advance enviropreneurial orientation (EO) as a new internal driver for green supply chain practice adoption. Because manufacturing supply chains are major contributors to environmental pollution, green practice adoption is a means of reducing environmental pollution. However, why owner/managers adopt green practices remains uncertain. The concept of EO is a potential and important motivation for adoption of green supply chain practices that has yet to be explored. The study investigates the relationship between EO and green supply chain practice adoption.

Design/methodology/approach

– Cross-sectional survey design was employed to collect data from owners/managers of SME manufacturing firms in Uganda. The structural equation modelling was used to analyse results on the influence of each of nine EO on green supply chain practice adoption and the influence of EO dimensions on green supply chain practice adoption.

Findings

– Findings show that EO positively influences green supply chain practice adoption. All but two of nine dimensions of EO were significant predictors of green supply chain practice adoption. Competitive aggressiveness and perceived pressure from environmental regulations were not significant predictors for green supply chain practice adoption.

Research limitations/implications

– The study was cross-sectional. A longitudinal survey was more appropriate because of the presence of a behavioural variable green supply chain practice adoption. Further a comparative study is required because of the existence of differences in classifications of SMEs in both the developing and developed countries.

Originality/value

– The research contributes to further scholarly understanding of green practice adoption in SMEs through offering a new construct, EO, and its role in influencing green supply chain practice adoption. The authors develop EO as a construct, a concept that has not been developed for more than two decades.

Online retail returns management

Purpose

– With the rapid growth of consumer sales being fulfilled through omni-channel retailing, the purpose of this paper is to explore the subsequent impact on the levels of consumer retail returns experienced through online sales and the emergent returns management strategies being affected by retailers in relation to network configuration and returns management processes.

Design/methodology/approach

– The authors uses a mixed methods approach from an interpretive perspective. It is appropriate to describe the approach in terms of convergent design, since the authors have collected both qualitative and quantitative data.

Findings

– Return rates for online retailing can be double those for stores, while return levels for “considered purchases” remain similar. The findings suggest that omni-channel returns management has yet to fully mature and the authors find challenges for network design and returns processes in offering a seamless solution.

Research limitations/implications

– For practitioners the authors identify a number of challenges and offer insights to improve performance in returns management process, while for academic colleagues the authors propose a number of avenues for further research both in the qualitative and quantitative fields.

Originality/value

– While a significant body of extant literature exists, in researching the generalized retail returns management process this paper make a contribution by addressing the emergent managerial implications of omni-channel retail returns.

Strategic sourcing management’s mindset: strategic sourcing orientation and its implications

Purpose

– Recently, focus in strategic sourcing (SS) has shifted from the exchange of tangible goods toward the exchange of intangibles, such as specialized skills, knowledge, and processes. The purpose of this paper is to aim to delineate the domain of, and operationally test, strategic sourcing orientation (SSO); a management philosophy directed at identifying and meeting the needs and goals of SS.

Design/methodology/approach

– Using a mixed-methods research design and underpinned by a service dominant logic (SDL) inspired resource-based view (RBV), the authors first use the qualitative input of 41 top sourcing executives in four focus groups to derive four first-order “orientations” (learning, performance, planning, and relational-process) that were found to reflect SSO. Second, the authors propose a theoretically grounded operationalization of SSO derived from the qualitative data and extant literature. A sample of 174 top sourcing executives was used to test the proposed SSO and its impact on SS reputation, supplier management, and performance outcomes.

Findings

– The results indicate strong support for the theorized SSO and its impact on SS reputation and supplier management, and, consequently, on performance outcomes.

Originality/value

– While many firms encourage a culture to enable SS to realize enhanced performance, research has failed to provide a holistic account of this orientation. This study employs a mixed-methods research design to conceptualize and operationalize such orientation.

Using a multiple-informant approach in SCM research

Purpose

– The purpose of this paper is to review the current state of survey-based SCM research that employs a multiple-informant perspective. Recommendations on how to rigorously conduct such research are developed, strengths and limitations discussed, and opportunities for advancing the discipline through this approach identified.

Design/methodology/approach

– A systematic literature review (SLR) of 1,048 articles published in five leading SCM journals within a seven-year time frame is conducted.

Findings

– The review shows that multiple-informant studies are still largely under-represented. Yet this approach more accurately depicts the multi-faceted nature of SCM. Specific requirements of this approach need to be considered throughout the research process, from unit of analysis, sampling frame, and data collection to analytic strategy.

Research limitations/implications

– Taking into account the often complex, dynamic actor networks in which SCM phenomena are embedded may provide new insights, especially when controversial results have been found. This approach may also enrich the understanding of phenomena that have previously been examined only from a monadic perspective.

Originality/value

– The paper examines the low incidence of multiple-informant survey research in SCM, discusses how its application can advance the field, and provides guidance on how to effectively apply this approach to more fully understand complex SCM phenomena. It further shows that studies using multiple informants yield novel theoretical insights and valuable recommendations for decision makers on how to use the interfaces between different actors across functional and organizational borders.

Human resource management issues in supply chain management research

Purpose

– With today's increasing globalization and associated growing demand for talented supply chain managers, human resource management (HRM) in supply chain management (SCM) has emerged as a top priority for firms. However, a thorough analysis of HRM issues in SCM research has not been made so far. To address this gap this paper provides a systematic and comprehensive literature review. The purpose of this paper is threefold: to analyze HRM/SCM issues published in leading SCM journals, to identify different HRM research streams in the SCM literature and to propose areas for future research.

Design/methodology/approach

– This paper employs a systematic literature review methodology. The selected journal articles are categorized on the basis of an analytical framework that contains seven HRM/SCM research streams derived from the extant literature.

Findings

– The systematic literature review indicates a growing focus on HRM/SCM issues in recent years, a trend that is predicted to continue. Additionally, the study findings show that research has primarily emphasized certain popular categories while other crucial ones lack analysis.

Originality/value

– This paper presents a structured overview of 109 peer-reviewed articles published in leading academic journals from 1998 to 2014. The review structures extant HRM/SCM literature and highlights its critical importance in SCM research. Topical gaps in the literature are identified as areas for future research.