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International Journal of Productivity and Performance Management (IJPPM) is one of the prominent journals publishing on general management with a particular focus on performance management and productive sciences. The objective of this study is to provide an academic structure overview of the journal between 2004 and 2018 using bibliometric tools.

Data used for this study were extracted using the Scopus database. Bibliometric analysis using several bibliometric indicators are adopted to know the major trends and themes of the journal. Mapping of bibliographic data is carried using VOSviewer and Gephi software.

Authors: Most of the IJPPM contributors are affiliated to the UK and India. Journal Performance: It is gaining pre-eminence in terms of total citations as well as CiteScores. Main themes: Major themes published in the journal are “performance management”, “productivity”, “six sigma”, “lean” and “supply chain management”.

IJPPM's growing influence in the scientific community has generated the interest to analyse the journal's publication and growth pattern. Moreover, no such retrospective bibliometric study for IJPPM is conducted so far.

Managing risks is becoming a highly focused activity in the health service sector. In particular, due to the complex nature of processes in the pharmaceutical industry, several risks have been associated to its supply chains. The purpose of this paper is to identify and analyze the risks occurring in the supply chains of the pharmaceutical industry and propose a decision model, based on the Analytical Hierarchy Process (AHP) method, for evaluating risks in pharmaceutical supply chains (PSCs).

The proposed model was developed based on the Delphi method and AHP techniques. The Delphi method helped to select the relevant risks associated to PSCs. A total of 16 sub risks within four main risks were identified through an extensive review of the literature and by conducting a further investigation with experts from five pharmaceutical companies in Bangladesh. AHP contributed to the analysis of the risks and determination of their priorities.

The results of the study indicated that supply-related risks such as fluctuation in imports arrival, lack of information sharing, key supplier failure and non-availability of materials should be prioritized over operational, financial and demand-related risks.

This work is one of the initial contributions in the literature that focused on identifying and evaluating PSC risks in the context of Bangladesh. This research work can assist practitioners and industrial managers in the pharmaceutical industry in taking proactive action to minimize its supply chain risks. To the end, the authors performed a sensitivity analysis test, which gives an understanding of the stability of ranking of risks.

Sustainable consumption and production (SCP) assist managers to improve their operational efficiency while aiming at reducing the generation of waste. The purpose of this paper is to construct a structural model of the SCP practices in a supply chain context.

The work is based on the experience of supply chain professionals, a case study and literature review related to SCP. The present work recommends an assessment framework by prioritizing the SCP oriented practices using best-worst method.

The current work is an effort to understand the significance of SCP practices and to reveal their level of influence in developing a sustainable culture in value chains. Data for this work are derived from an automotive company operating in India. Findings reveal that the “resource efficiency” acquires the highest rank and “sharing assets” acquires the last lank among all SCP practices.

It is difficult to finalize the SCP practices. This work uses the expert’s approach for this. In this way, the process needs to be conducted very carefully.

This research can assist automotive managers and practitioners in efficiently utilizing their companies’ resources, which would result in superior business effectiveness by generating higher employment opportunities in value chains.

Efforts have been made to contribute in the identification and analysis of SCP oriented practices. The developed structural model will help in understanding the ranking of practices.

During pre-vaccine era, pharmaceutical supplies [self-care essentials (SCEs)] have been proved to be a major deflector, protector and safety guard against novel coronavirus disease (COVID-19). Hence, the objective of the study is to provide a comprehensive socio-technological decision-making framework based on multiple criteria for selecting the suppliers of pharmaceuticals, such as SCEs, by multi-brand enterprises (distributors) in the pandemic environment.

A hybrid methodology of Bayesian best worst method (BWM) and multi-attributive border approximation area comparison (MABAC) method has been applied for carrying out the study. Bayesian BWM has been applied for computing the importance of criteria identified for the selection of SCEs' suppliers during pandemic environment and MABAC method evaluated the suppliers of the SCEs.

In the study, the authors have identified eight criteria such as disinfection and sanitization of vehicles, social conscience of suppliers, brand (Technological recognition) of SCEs and logistics and distribution network, among others, which are critical to the selection of a supplier for the supply of SCEs. The application of the proposed hybrid model revealed that lead time and quality of SCEs are of utmost concern for pharmacies in a pandemic environment. Among the ten suppliers, results showed that Suppliers 2, 4 and 5 have been ranked first for supplying hand wash, hand sanitizer and face mask, respectively.

The proposed model has helped the multi-brand distributors of pharmaceuticals in selecting suppliers during the ongoing crisis of COVID-19. In addition to that, in future the outcomes of the study would be helpful for multi-brand distributors as well as pharmacies and hospitals in selecting the best suppliers. Policy makers will be able to make and revise the policies immediately with the help of the proposed decision-making framework.

The paper makes a novel contribution towards theory with the criteria identified for selecting best suppliers during the pandemic COVID-19. Additionally, the proposed hybrid model helps multi-brand distributors of pharmaceuticals in making decisions that lead to a huge social and economic success in pandemic time.

The paper aims to identify key human and operational focused barriers to the implementation of Total Quality Management (TQM). It develops a comprehensive structural relationship between various barriers to successfully implement TQM for sustainability in Indian organizations.

With the help of expert opinions and extant literature review, we identified the case of TQM failure companies and barriers to implement TQM effectively. Interpretive Structural Modeling (ISM) and fuzzy MICMAC techniques are employed to develop a structural model and the identified barriers are categorized based on their dependence and driving power in the various categories.

From the intensive case analysis, we identify fourteen barriers that constrain the successful implementation of TQM. The findings also provide a hierarchy of barriers in which the absence of top management involvement and ineffective leadership are the human barriers having the highest dependence.

The critical inputs show the implementation of TQM in the firms being more proactive and well prepared in the selected five companies. The study's emphasis on barriers will help organizations in implementing TQM for better sustainability in an organizational context.

In the successful implementation of TQM, barriers need to be identified because failure has often eliminated the organizations from the market. Thus, TQM is the source of strength to achieve higher productivity, profitability, and sustainable business performance. The barriers must be identified to improve organizational performance to contribute to sustainable development.

Food supply chains (FSCs) are fast becoming more and more complex. Sustainability is a necessary strategy in FSCs to meet the environmental, economic and societal requirements. Industry 4.0 (I4.0) applications for a circular economy (CE) will play a significant role in sustainable food supply chains (SFSCs). I4.0 applications can be used in for traceability, tracking, inspection and quality monitoring, environmental monitoring, precision agriculture, farm input optimization, process automation, etc. to improve circularity and sustainability of FSCs. However, the factors integrating I4.0 and CE adoption in SFSC are not yet very well understood. Furthermore, despite such high potential I4.0 adoption is also met with several barriers. The present study identifies and analyzes twelve barriers for the adoption of I4.0 in SFSC from an CE context.

A cause-effect analysis and prominence ranking of the barriers are done using Rough-DEMATEL technique. DEMATEL is a widely used technique that is applied for a structured analysis of a complex problems. The rough variant of DEMATEL helps include the uncertainty and vagueness of decision maker related to the I4.0 technologies.

“Technological immaturity,” “High investment,” “Lack of awareness and customer acceptance” and “technological limitations and lack of eco-innovation” are identified as the most prominent barriers for adoption of I4.0 in SFSC.

Successful mitigation of these barriers will improve the sustainability of FSCs through accelerated adoption of I4.0 solutions. The findings of the study will help managers, practitioners and planners to understand and successfully mitigate these barriers.

The purpose of this paper is to facilitate green supply chain (GSC) managers and planners to model and access GSC risks and probable failures. This paper proposes to use the fuzzy failure mode and effects analysis (FMEA) approach for assessing the risks associated with GSC for benchmarking the performance in terms of effective GSC management adoption and sustainable production.

Initially, different failure modes are defined using FMEA analysis, and in order to decide the risk priority, the risk priority number (RPN) is determined. Such priority numbers are typically acquired from the judgment decisions of experts that could contain the element of vagueness and imperfection due to human biases, and it may lead to inaccuracy in the process of risk assessment in GSC. In this study, fuzzy logic is applied to conventional FMEA to overcome the issues in assigning RPNs. A plastic manufacturer GSC case exemplar of the proposed model is illustrated to present the authenticity of this method of risk assessment.

Results indicate that the failure modes, given as improper green operating procedure, i.e. process, operations, etc. (R6), and green issues while closing the loop of GSC (R14) hold the highest RPN and FRPN scores in classical as well as fuzzy FMEA analysis.

The present research work attempts to propose an evaluation framework for risk assessment in GSC. This paper explores both sustainable developments and risks related to efficient management of GSC initiatives in a plastic industry supply chain context. From a managerial perspective, suggestions are also provided with respect to each failure mode.