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This paper aims to develop a performance measurement (PM) system for fourth-party reverse logistics (RL). In this regard, it proposes simultaneous utilization of a procedural approach and hybrid use of existing performance frameworks.

The paper first describes fundamentals of RL and PM approaches in literature to build a basis for further discussion. It then carries out a systematic review of the literature on PM in RL to highlight current trends and approaches in this regard. At last, it develops a PM system for fourth-party RL by exploring relevant performance frameworks and by defining a procedure in detail.

The paper identifies the ongoing interest in development PM in RL, and the gap and the need for the development of comprehensive PM system for fourth-party RL. It also identifies the best approach is to use existing performance frameworks in literature and a procedural approach together as they complement each other rather than contradicting.

The paper fills a gap in literature by developing a comprehensive PM framework for the fourth-party RL. The presented procedure is well suited to be used as part of strategic management process in any fourth-party RL organization. It forces users a top-down approach, from strategies to measures, so that a strong linkage is established in the process. When used together with the proposed PM framework, it guarantees a comprehensive and balanced PM system.

The paper identifies the need for the development of a PM framework as well as a measurement system for the fourth-party RL in the literature. In this regard, it develops a PM framework first, and then a procedure on how to implement it. As a result, users can effectively use them as a part of strategic management process of their organizations.

The fourth-party RL is growing and very promising mode of RL for well-being of society, by offering a strong path to sustainable development in the midst of diminishing resources in the world. The existence of a well measurement system is crucial for the healthy operations and development of fourth-party RL organizations. The paper is offering a strong PM model in this regard.

The paper fulfills an identified need to study how to develop a PM system for fourth-party RL.

Managerial practices are essential in the success of information technology (IT) projects of digital transformation (DT). However, the literature has not yet specified all these managerial practices. This study aims to address this gap by investigating the influence of change management on the success of IT projects of DT. Additionally, the author examines the consequences on SMEs in the economic context of the Democratic Republic of the Congo (DRC).

This study draws on a research model that elucidates aspects of the resource-based view (RBV) framework, notably the transformation of human resources based on change management. This model demonstrates the relationship between change management, DT and IT project success, which facilitates the performance and resilience of SMEs. To empirically validate and test the developed research model, we gathered 299 responses from SME managers in the DRC through cross-sectional data collection using a structured questionnaire. The author performed statistical analyses using variance-based structural equation modeling (PLS-SEM) with the help of SmartPLS 3.0.

This paper reveals how SME managers can succeed in DT projects with the change management of human resources. Furthermore, it establishes that the success of IT projects of DT is an essential for enhancing the performance and resilience of SMEs in the DRC.

This study contributes to the information systems (IS) literature on developing countries by highlighting the DRC context. Little research deals with the success factors of DT projects and their organizational impact on SMEs in developing countries. This study thus enriches the IS literature by filling this void.

In the current era, the focus on circular economy (CE) has gained substantial momentum among the research communities across the manufacturing world. It has become the need of the hour to act fast due to the alarming issues of unsustainability such as climate change, global warming, waste generation, environmental pollution, resource scarceness and ecological degradations. This research aims to investigate and model the CE enablers in the product development process related to the moderating effect of net zero.

The significant CE enablers are identified through literature review and expert brainstorming. The Pythagorean fuzzy decision-making trial and evaluation laboratory (PF-DEMATEL) technique has been used to investigate and evaluate the significant CE enablers in product development process. PF-DEMATEL determines the inter-relationship and casual dependency among the selected CE enablers. Indian automobile small and medium enterprises (SMEs) have been considered as a case organization to demonstrate the effectiveness of the proposed method.

The findings reveal that “Top management support and clear vision towards CE adoption” is the most important enabler and “Artificial intelligence in product value chain” is recognized as the least vital enabler. This research aids the managers, decision-makers, policy planners and workforce to develop and formulating efficient blueprints for the effective adoption of CE in Indian SMEs.

This is the first kind of research that explores CE enablers in product development process for Indian SMEs.

Mixed methods research is useful to enhance theoretical and practical research contributions. However, single methods have predominated much logistics and supply chain management (LSCM) research. This paper presents a review of mixed methods research across ten years in LSCM to determine their usage, identify benefits and inhibitors, and provide suggestions for LSCM researchers to realise the benefits from using mixed methods.

This paper adopts a mixed methods approach through a quantitative analysis of methods used in six leading LSCM journals, an e-mail survey of mixed methods article authors during the review period, and four published case studies that used mixed methods.

Only 144 (ten percent) of all empirical articles were published using mixed methods during the review period. A range of benefits and inhibitors regarding mixed methods adoption were found. Suggestions for LSCM authors include research training in mixed methods use and developing a project-specific research design due to the specificity and complexity associated with mixed methods research.

LSCM is at a critical juncture, shaped by new contexts, themes and challenges, and would benefit from different research approaches and methods. This paper contributes to the LSCM domain through analysing the current state, benefits and inhibitors of mixed methods research in LSCM journals to provide a renewed call to action and guidelines for mixed methods LSCM research, and suggesting research design adaptation to enable agile and resilient research when investigating rapidly changing and complex phenomena.

This paper aims to investigate the characteristics and dynamics of the organizational changes needed to facilitate the management of an Industry 4.0 transformation in manufacturing SMEs and propose an approach to manage them.

This research focuses on a single manufacturing SME in North America, and data were collected using a research intervention method. Data were collected through observation and intervention within the SME over 27 months.

The research has shown that organizational changes are required in manufacturing SMEs to better manage their Industry 4.0 transformation projects.

Using the case study method limits the generalization of the results. The organizational changes observed, and their characteristics might be specific to the studied manufacturing. Although results could vary in different contexts, many manufacturing SMEs have similar characteristics to those observed in this study.

This research provides preliminary evidence of an iterative organizational change management approach that manufacturing SMEs must adopt to facilitate the management of their digital transformation.

This research provides a better understanding of how a manufacturing SME can improve its capabilities to manage its digital transformation by introducing iterative organizational changes. From these results, a link to the organizational learning literature can be drawn and developed upon.

The integration of sustainability, performance measurement and new product development (NPD) is key for aligning environmental and social objectives with business strategies. While previous research has initiated proposals for integrating sustainability into NPD or incorporating sustainability into corporate measurement systems, there is a notable deficiency in studies that comprehensively integrate these three perspectives. In this sense, this study proposes a performance framework (PF) to integrate sustainability performance indicators (PIs) into the measurement system considering the company’s NPD phases.

The PF was developed through a literature review and action research (AR). This resulting PF was positively evaluated by the practitioners in the company.

First, the review enabled the synthesis of an initial conceptual PF with 188 sustainability PIs and a five-step procedure. Then, the empirical results of the AR led to a new PF that presents the systematisation of the PIs database and a practice-based seven-stage approach.

This action-oriented research limits the extent to which this study’s findings can be generalised. Future research should apply the PF in different research designs to produce managerially relevant knowledge.

This PF may provide managers with actionable knowledge that best supports the measurement system integration with sustainability PIs considering the NPD phases.

Integrating sustainability, performance measurement and the NPD has been recognised as critical for supporting decision-making concerning the impact of processes and products. Compared with previous frameworks, the proposed PF extends the existing literature by introducing a systematised PIs database and a novel procedure for integrating sustainability measurement throughout the NDP.

Modular construction is an innovative method that enhances the performance of building construction projects. However, the performance of steel modular construction has not been systematically understood, and the existing measurement methods exhibit limitations in effectively addressing the features of steel modular building construction. Therefore, this study aims to develop a new performance measurement framework for systematically examining the performance of steel modular construction in building projects.

This study was conducted through a mixed-method research design that combines a comprehensive review of the state-of-the-art practices of construction performance measurement and a case study with a 17-story steel modular apartment building project in Hong Kong. The case project was measured with data collected from the project teams and other reliable channels, and the measurement practices and findings were referenced to establish a systematic performance measurement framework for steel modular construction.

Considering steel modular construction as a complex socio-technical system, a systematic performance measurement framework was developed, which considers the features of steel modular construction, focuses on the construction stage, incorporates the views of various stakeholders, integrates generic and specific key performance indicators and provides a benchmarking process. Multifaceted benefits of adopting steel modular construction were demonstrated with case study, including improved economic efficiency (e.g. nearly 10% cost savings), improved environmental friendliness (e.g. approximately 90% waste reduction) and enhanced social welfare (e.g. over 60% delivery trips reduction).

This paper extends the existing performance measurement methods with a new framework proposed and offers experience for future steel modular construction. The measured performance of the case project also contributes in-depth understanding on steel modular construction with benefits demonstrated. The study is expected to accelerate an effective uptake of steel modular construction in building projects.

This paper aims to improve our understanding of performance measurement systems in the health and care sector, by focussing on employee reactions to core performance measurement practices. Targets and monitoring are hypothesised to be associated with employee perceptions of job control, supportive management and job demands, which in turn, are expected to be linked to employee-wellbeing and organisational commitment.

Matched employee workplace data are extracted from a nationally representative and publicly available survey. Structural equation models are estimated.

Performance measurement systems are neither perceived as resources nor additional demands. Setting many targets and a focus on productivity can lead to negative employee outcomes, since these positively correlate with perceptions of job demands, which negatively correlate with employee wellbeing. However, monitoring financial performance and monitoring employee performance may be helpful to managers, as these are positively associated with employee perceptions of job control and supportive management, which positively correlate with job satisfaction and organisational commitment and, negatively, with anxiety. Overall, common criticisms of performance measurement systems in healthcare are questioned.

Given the lack of consensus on how performance measurement systems can influence employee experiences and outcomes, this study combines theories that argue for performance measurement systems in managing operations with models developed by psychologists to describe how perceptions of the work conditions can affect employee attitude and wellbeing. A conceptual model is therefore developed and tested, and potential direct and indirect effects of performance measurement systems in the health sector are inferred.

The view that dynamic capabilities theory can help explain how lean organizations improve has been put forward by scholars. However, there is still a lack of research on the matching relationship between the application of lean practice and the internal elements of enterprise organization from the perspective of dynamic capabilities. The purpose of this study is to validate the moderating effect of dynamic capabilities on the relationship between lean practices and operational performance.

This study used the method of survey and empirical research to collect sample data from 263 enterprises in China. Through literature review, this study put forward the moderating hypotheses around dynamic capabilities, lean practices and operation performance and used the method of regression analysis to validate these hypotheses.

The results showed that dynamic capabilities have a partially moderating effect on the application of lean practices. Specifically, dynamic capabilities have a significant moderating effect on the relationship between just-in-time, total quality management, total preventive maintenance and operational performance, while dynamic capabilities have no significant moderating effect on the relationship between human resource management and operational performance.

The research conclusion complements and enriches the lean practices literature from the perspective of dynamic capabilities. Existing studies mainly focus on the moderating role of external environmental factors, while there is a lack of empirical research on the role of dynamic capabilities in lean practices literature. The research results will help enterprises further understand the matching relationship between lean practices and dynamic capabilities and then improve the success of lean practices application.

This paper proposes a progressive, multi-level framework for diagnosing maintenance performance: rapid performance health checks of key performance for different equipment groups and end-to-end process diagnostics to further locate potential performance issues. A question-based performance evaluation approach is introduced to support the selection and derivation of case-specific indicators based on diagnostic aspects.

The case research method is used to develop the proposed framework. The generic parts of the framework are built on existing maintenance performance measurement theories through a literature review. In the case study, empirical maintenance data of 196 emergency shutdown valves (ESDVs) are collected over a two-year period to support the development and validation of the proposed approach.

To improve processes, companies need a separate performance measurement structure. This paper suggests a hierarchical model in four layers (objective, domain, aspect and performance measurement) to facilitate the selection and derivation of indicators, which could potentially reduce management complexity and help prioritize continuous performance improvement. Examples of new indicators are derived from a case study that includes 196 ESDVs at an offshore oil and gas production plant.

Methodological approaches to deriving various performance indicators have rarely been addressed in the maintenance field. The proposed diagnostic framework provides a structured way to identify and locate process performance issues by creating indicators that can bridge generic evaluation aspects and maintenance data. The framework is highly adaptive as data availability functions are used as inputs to generate indicators instead of passively filtering out non-applicable existing indicators.