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This paper aims to examine how interfirm transactional and relational assets drive firm performance (FP) in digitally integrated supply chains.

The authors combine the Transaction Cost Economics (TCE) and Relational Exchange Theory (RET) frameworks to hypothesize that FP will be a function of Asset Specificity (AS), Digital Technology Usage (DTU) and Collaborative Information Sharing (CIS). In addition, the authors hypothesize that Supply Chain Integration (SCI) will partially mediate the effect of DTU and fully mediate the impact of AS and CIS on FP. A cross-sectional survey of supply chain managers is used to test the hypotheses.

Findings indicate that specific investments in digitally integrated supply chains would increase FP. In addition, SCI fully mediates the relationships between AS and FP and CIS and FP, while SCI partially mediates the influence of DTU on FP.

Managers could strategically engage in the technologies that effectively fit within the firm’s supply chain strategies and seek to develop a pragmatic expertise that enables the effective use of technology in a comprehensive setting.

The study enriches the extant literature by incorporating TCE and RET as contradictory viewpoints on AS and investigating how transactional and relational assets affect FP in digitally integrated supply chains.

Absorptive capacity (AC), the ability to leverage external knowledge for innovation, helps explain the mixed findings on family firms' (FFs) innovation performance. Our research focuses on the chief executive officer (CEO)’s role – whether family or non-family and founding or later generation – in influencing AC. We also explore how firm size and environmental dynamism affect these relationships, offering insights into varying AC levels among FFs.

Ordinary least squares (OLS) regression models were estimated to test the hypotheses using a sample of 364 FFs in Spain.

FFs’ AC is greater when the CEO is a family member, and even more so when the family CEO belongs to the founding family generation. While AC diminishes in larger FFs, this effect is mitigated when the CEO is a family member. The predicted moderating effect of environmental dynamics is not supported by the analyses.

This paper adds insights about the drivers of heterogeneity in innovation among FFs, addressing recent calls for more nuanced views of how family members drive the strategic behavior of the business and incorporating considerations of different types of FFs based on the identity of the firm CEO. The results overall support the theoretical claims and also open up important questions for future studies.

This research paper aims to analyze the scientific and grey literature on Quality 4.0 and zero-defect manufacturing (ZDM) frameworks to develop an integrated quality 4.0 framework (IQ4.0F) for quality improvement (QI) based on Six Sigma and machine learning (ML) techniques towards ZDM. The IQ4.0F aims to contribute to the advancement of defect prediction approaches in diverse manufacturing processes. Furthermore, the work enables a comprehensive analysis of process variables influencing product quality with emphasis on the use of supervised and unsupervised ML techniques in Six Sigma’s DMAIC (Define, Measure, Analyze, Improve and Control) cycle stage of “Analyze.”

The research methodology employed a systematic literature review (SLR) based on PRISMA guidelines to develop the integrated framework, followed by a real industrial case study set in the automotive industry to fulfill the objectives of verifying and validating the proposed IQ4.0F with primary data.

This research work demonstrates the value of a “stepwise framework” to facilitate a shift from conventional quality management systems (QMSs) to QMSs 4.0. It uses the IDEF0 modeling methodology and Six Sigma’s DMAIC cycle to structure the steps to be followed to adopt the Quality 4.0 paradigm for QI. It also proves the worth of integrating Six Sigma and ML techniques into the “Analyze” stage of the DMAIC cycle for improving defect prediction in manufacturing processes and supporting problem-solving activities for quality managers.

This research paper introduces a first-of-its-kind Quality 4.0 framework – the IQ4.0F. Each step of the IQ4.0F was verified and validated in an original industrial case study set in the automotive industry. It is the first Quality 4.0 framework, according to the SLR conducted, to utilize the principal component analysis technique as a substitute for “Screening Design” in the Design of Experiments phase and K-means clustering technique for multivariable analysis, identifying process parameters that significantly impact product quality. The proposed IQ4.0F not only empowers decision-makers with the knowledge to launch a Quality 4.0 initiative but also provides quality managers with a systematic problem-solving methodology for quality improvement.

The application of lean and quality improvement methods is very common in process improvement projects at organisational levels. The purpose of this research is to assess the adoption of Lean Six Sigma™ approaches for addressing a complex process-related issue in the coal industry.

The sticky coal problem was investigated from the perspective of process-related issues. Issues were addressed using a blended Lean value stream of supply chain interfaces and waste minimisation through the Six Sigma™ DMAIC problem-solving approach, taking into consideration cross-organisational processes.

It was found that the tendency to “solve the problem” at the receiving location without communication to the upstream was, and is still, a common practice that led to the main problem of downstream issues. The application of DMAIC Six Sigma™ helped to address the broader problem. The overall operations were improved significantly, showing the reduction of sticky coal/wagon hang-up in the downstream coal handling terminal.

The Lean Six Sigma approaches were adopted using DMAIC across cross-organisational supply chain processes. However, blending Lean and Six Sigma methods needs to be empirically tested across other sectors.

The proposed methodology, using a framework of Lean Six Sigma approaches, could be used to guide practitioners in addressing similar complex and recurring issues in the manufacturing sector.

This research introduces a novel approach to process analysis, selection and contextualised improvement using a combination of Lean Six Sigma™ tools, techniques and methodologies sustained within a supply chain with certified ISO 9001 quality management systems.

Multinational business deliver value via multiple sites with similar operational capacities. The age of the Fourth Industrial Revolution (4IR) delivers significant opportunities for the deployment of digital tools for business optimization. Therefore, this study aims to study the Industry 4.0 implementation for multinationals.

The key objective of this research is multi-site systems integration using a reproducible, modular and standardized “Cyber Physical System (CPS) as-a-Service”.

A best practice reference architecture is adopted to guide the design and delivery of a pioneering CPS multi-site deployment. The CPS deployed is a cloud-based platform adopted to enable all manufacturing areas within a multinational energy and petrochemical company. A methodology is developed to quantify the system environmental and sustainability benefits focusing on reduced carbon dioxide (CO₂) emissions and energy consumption. These results demonstrate the benefits of standardization, replication and digital enablement for multinational businesses.

The research illustrates the ability to design a single system, reproducible for multiple sites. This research also illustrates the beneficial impact of system reuse due to reduced environmental impact from lower CO₂ emissions and energy consumption. The paper assists organizations in deploying complex systems while addressing multinational systems implementation constraints and standardization.

The digital warehouse management system is an emergence that forms a critical part of the transformation of economic structure in Industry 4.0. In the present business scenario, the warehouse management system encounters a messy layout, poor damage control, unsatisfactory order management, lack of visibility and lack of technological interventions. Digital twin (DT) based warehouse system shows the ontology and knowledge graphs for competitive advantage by consolidating and transferring goods directly from an inbound supplier to an outbound customer on short notice and with no or limited storage. There remains a lack of clarity on how the DT can be implemented successfully in warehouse management.

The current literature remains largely unstructured and scattered due to a lack of a systematic approach to integrating the research implications and analysis. This paper probes the conceptualization of the DT with the help of theoretical analysis using the systematic literature analysis method.

The study explores essential concepts such as interoperability and integrability in implementing DT. Further, it analyzes the role of a supply chain control tower (SCCT) in modern supply chain management. A research framework is proposed for practitioners and academicians by incorporating the opportunities and challenges associated with DT implementation. The research findings are mainly threefold: Conceptualization of DT, Featuring SCCT and Exploration of cross-computer platform interfaces, scalability and maintenance strategies.

This study is among the first to analyze and review DT applications in warehouse management. Moreover, the study proposes a theoretical toolbox for the practitioners to successfully implement the DT in warehouse DT-based warehouse management system: A theoretical toolbox for future research and applications.

This study aims to analyse the influence of digitalisation on the management control function of small and medium-sized enterprises (SMEs). In particular, it aims to illuminate how digitalisation influences management control elements, organisation and roles/competencies and to identify obstacles to digitalisation of management control in SMEs and measures taken to overcome them.

The study is based on guideline-supported expert interviews conducted with 14 financial managers from SMEs in Germany, Austria and Switzerland.

This study reveals the influence of digitalisation on management control elements, organisation, and roles/competencies. The automation and standardisation of management control processes result in new elements for management control, such as strategic support for management. In addition, the increased availability and transparency of data enable the use of instruments within a company that allow for quick analyses of the company's development. Digitalisation leads to the integration of management control into the corporate network and, thus, a change in the organisation of management control. It also triggers the expansion of management control competencies, especially IT competencies. A shortage of internal digitalisation resources, unclear corporate roadmaps, and a lack of managerial experience loom as central challenges for digitalising the management control function. Measures derived from the interviews can help SMEs overcome the obstacles to the digitalisation of management control.

This research is the first interview-based study of the impact of digitalisation on management control in SMEs, potential obstacles to that digitalisation, and measures to overcome those obstacles. Thus, it contributes to the emerging debate on factors that may explain why SMEs lag in terms of the digitalisation of their internal processes.

To address the absence of Lean in transportation logistics in the digital era, this study aims to investigate the application of Lean transportation (LT) tools to reduce waste and facilitate the digital transformation of dedicated road transportation in the offshore industry.

The study adopts action research with a multimethod approach, including a scoping review, focus groups (FG) and participant observation. The research is conducted within the offshore supply chain of a major oil and gas company.

Implementing LT’s continuous improvement tools, particularly value stream mapping (VSM), reduces offshore transportation waste and provides empirical evidence about the intersection of Lean and digital technologies. Applying techniques drawn from organisational learning theory (OLT), stakeholders involved in VSM mapping and FGs engage in problem-solving and develop action plans, driving digital transformation. Waste reduction in loading and unloading stages leads to control actions, automation and process improvements, significantly reducing downtime. This results in an annual monetary gain of US$1.3m. The study also identifies waste related to human effort and underutilised digital resources.

This study contributes to theory and practice by using action research and LT techniques in a real intervention case. From the lens of OLT, it highlights the potential of LT tools for digital transformation and demonstrates the convergence of waste reduction through Lean and Industry 4.0 technologies in the offshore supply chain. Practical outputs, including a benchmarking questionnaire and a plan-do-check-act cycle, are provided for other companies in the same industry segment.

The industrial revolution changed the market landscape significantly in all industrial sectors. It has a noteworthy impact on enhancing the quality of goods and services. The quality aspect is of utmost concern and determines the success or failure of any product. Therefore, the presented study analyses the key barriers and solutions of Quality 4.0.

Twenty barriers and fifteen solutions were identified using a literature review and investigated using a hybrid approach. Barrier weights were evaluated with the help of the fuzzy AHP method. Furthermore, the computed weights were used to perform computations in the next step using fuzzy-TOPSIS to prioritize the ranking of identified solutions.

The research results show that “Lack of applying advanced analytics to uncover Quality 4.0 initiatives” and “Lack of integrating data from various sources across the organization” are the topmost barriers. Furthermore, “Implement a leadership development program focused on Quality 4.0” and “Cross-departmental peer learning environment” are the topmost solutions.

Managers and industrialists can benefit from Quality 4.0 through improved decision-making, process efficiency, supply chain collaboration, agile quality management, enhanced customer experience and a culture of continuous improvement. This results in better quality, operational effectiveness and a competitive edge.

The solutions need to be mapped with barriers to adopting Quality 4.0. Furthermore, the research results involve novelty by prioritizing the solutions to overcome the anticipated barriers.

The study aims to test the success of university-industry (U-I) collaboration in terms of innovation process efficiency. Then, this study explores the moderating role of a set of organizational routines in the U-I relationship, which can help in overcoming the issues undermining the collaboration success.

The study is based on an international Open Innovation (OI) survey. The survey investigated the items to build the main variables of the conceptual framework, measured through seven-point Likert scales. Steps to ensure the reliability and validity of the variables were conducted. Then, hypotheses were tested with an ordinary least squares regression.

Results show that the higher the collaboration intensity (depth) with universities, the higher the innovation process efficiency. Furthermore, organizational routines aimed at improving firms' assimilation absorptive capacity further strengthen the positive effects of intensive collaboration on innovation process efficiency.

Findings indicate that R&D managers should strive to build deep collaborations with universities to enhance process efficiency and invest in the quality of these relationships. Managers should create and maintain an internal environment that further enhances the positive effects of intensive collaboration on innovation process efficiency.

The OI literature has not reached a shared view on the positive contribution of universities toward industrial firms' innovation performance. The study adopts a process-efficiency view, rarely used by other OI studies usually focused on output indicators; this study unpacks, respectively, the role of the intensity of collaboration and the organizational routines, thus disclosing the benefit of U-I collaboration on innovation efficiency.