Search results

Despite differing strategies towards environmental sustainability in developed and developing nations, the manufacturing sector in these regional domains faces substantial environmental issues. The purpose of this study is to examine the green-lean-six sigma (GLSS) enablers and outcomes for enhancing environmental sustainability of manufacturing firms in both, a developed and developing country context by using an environment-centric natural resource-based view (NRBV).

First, a framework of GLSS enablers and outcomes aligned with the NRBV strategic capabilities is proposed through a systematic literature review. Second, this framework is used to empirically investigate the GLSS enablers and outcomes of manufacturing firms through in-depth interviews with lean six sigma and environmental consultants from New Zealand (NZ) and Pakistan (PK) (developed and developing nations).

Analysis from both regional domains highlights the use of GLSS enablers and outcomes under different NRBV capabilities of pollution prevention, product stewardship and sustainable development. A comparison reveals that NZ firms practice GLSS to comply with environmental regulatory requirements, avoid penalties and maintain their clean-green image. Conversely, Pakistani firms execute GLSS to reduce energy use, satisfy international customers and create a green image.

This paper provides new insights on GLSS for environmental sustainability which can assist industrial experts and academia for future strategies and research.

This is one of the early comparative studies that has used the NRBV to investigate GLSS enablers and outcomes in manufacturing firms for enhancing environmental performance comparing developed and developing nations

Measuring shared value (SV) created in innovation ecosystems (IEs) is increasingly relevant but complex, given the multidimensional and multiactor nature of both concepts, which challenges traditional performance measurement systems (PMSs). Moving from this gap, the authors propose an integrated approach to extend the balanced scorecard (BSC) for measuring and monitoring SV creation at IE level.

The proposed approach combines the most recent contributions on PMS in IEs and SV to define perspectives and dimensions that are better suited to deal with the nature of both IEs and SV. The approach is also applied to the real case (Alpha) of an Italian IE through a step wise method. Starting from the IE vision, the authors identify in the strategy map the specific objectives related to each perspective/dimension combination and then associate a performance indicator with each objective.

The resulting SV BSC is composed of indicators interconnected along different perspectives and dimensions. The application of the approach to the real case proves its feasibility and highlights characteristics, advantages and disadvantages of the SV BSC when used at IE level. The authors also provide guidelines for its application to other IEs.

The study contributes to the research on PMS by introducing and applying to a real case an integrated approach to assess SV in IEs, overcoming the shortcomings of PMS framed for single firms. It can be of interest for both researchers in the field of ecosystems value creation and practitioners managing or promoting such complex structures.

Today’s marketplace has witnessed intense competitive pressures and high levels of uncertainty and disruption. Therefore, supply chains require agility to obtain a sustainable competitive advantage and cope with uncertainties as well as disruptions. Although a wide range of studies exists on supply chain agility (SCA) from the perspective of antecedents or consequences, there is little research on the investigation of enablers of SCA and their relations among them. Furthermore, the literature has investigated proactive and reactive enablers for enhancing SCA, but most studies have not sufficiently framed their analysis of both aspects synchronically. This paper aims to find out the interrelationships among the proactive and reactive enablers for enhancing SCA.

An extensive literature review has been conducted to identify SCA enablers and a Delphi study has been performed to elucidate SCA enablers in the manufacturing industry in Turkey. Interpretive structural modeling (ISM) has been used to identify the contextual relationship among the SCA enablers, and the model has been validated based on Matriced Impact Croises Multiplication Appliquee a un Classement (MICMAC) analysis.

On theoretical and practical levels, the proposed ISM model in this study can help organizations analyze and interpret interrelationships among enablers of SCA. For managers, it can provide better insights and understanding of the facilitators of SCA to enhance the effectiveness of the supply chain and cope with uncertainties and turbulence. According to results, enhancing “supply and demand side competency”, “delivery speed” and “strategic sourcing” are the most significant enablers of SCA.

The study extends the existing literature related to the enablers of SCA by modeling the proactive and reactive enablers of SCA based on the Al Humdan et al. (2020) classification. Arranging the enablers of SCA in a hierarchy and classifying the enablers into different levels with the help of the ISM-MICMAC approach is an exclusive effort to achieve successful management of the supply chain.

The automotive industry appears to overcome much of its obstacles, despite the constant struggle facing COVID-19. The pandemic has resulted in significant improvements in the habits and conduct of consumers. There is an increased preference for personal mobility. In this dynamic environment with unexpected changes and high market rivalry, automotive supply chains focus more on executing responsive strategies with minimum costs. This paper aims to identify and model the drivers to the responsiveness of automotive supply chain.

Seventeen drivers for supply chain responsiveness have been identified from the extensive literature, expert interview. An integrated methodology of fuzzy decision-making trial and evaluation laboratory–interpretive structural modelling (DEMATEL–ISM) is developed to establish the interrelationship between the drivers. The cause–effect relationship between the drivers was obtained through fuzzy DEMATEL technique, and a hierarchical structure of the drivers was developed using the ISM technique.

The result of the integrated methodology revealed that strategic decision-making of management, accurate forecasting of demand, advanced manufacturing system in the organisation and data integration tools are the critical drivers.

This study has conceptual and analytical limitations. In this study, a limited number of drivers are examined for supply chain responsiveness. Further research may examine the role of other key performance indicators in the broad field of responsiveness in the automotive supply chain or other industry sectors. Future study can uncover the interrelationships and relative relevance of indicators using advanced multi-criteria decision-making methodologies.

The authors proposed an integrated methodology that will be benefitted to the supply chain practitioners and automotive manufacturers to develop management strategies to improve responsiveness. This study further helps to compare the responsiveness of the supply chain between various automotive manufacturers.

Managers must make numerous strategic decisions in order to initiate and implement a business model innovation (BMI). This paper examines how managers perceive the management team interacts when making BMI decisions. The paper also investigates how group biases and board members’ risk willingness affect this process.

Empirical data were collected through 26 in-depth interviews with German managing directors from 13 companies in four industries (mobility, manufacturing, healthcare and energy) to explore three research questions: (1) What group effects are prevalent in BMI group decision-making? (2) What are the key characteristics of BMI group decisions? And (3) what are the potential relationships between BMI group decision-making and managers' risk willingness? A thematic analysis based on Gioia's guidelines was conducted to identify themes in the comprehensive dataset.

First, the results show four typical group biases in BMI group decisions: Groupthink, social influence, hidden profile and group polarization. Findings show that the hidden profile paradigm and groupthink theory are essential in the context of BMI decisions. Second, we developed a BMI decision matrix, including the following key characteristics of BMI group decision-making managerial cohesion, conflict readiness and information- and emotion-based decision behavior. Third, in contrast to previous literature, we found that individual risk aversion can improve the quality of BMI decisions.

This paper provides managers with an opportunity to become aware of group biases that may impede their strategic BMI decisions. Specifically, it points out that managers should consider the key cognitive constraints due to their interactions when making BMI decisions. This work also highlights the importance of risk-averse decision-makers on boards.

This qualitative study contributes to the literature on decision-making by revealing key cognitive group biases in strategic decision-making. This study also enriches the behavioral science research stream of the BMI literature by attributing a critical influence on the quality of BMI decisions to managers' group interactions. In addition, this article provides new perspectives on managers' risk aversion in strategic decision-making.

This study aims to: (1) investigate the relationship/connection between organizational change (OC) and organizational resilience (OR) and (2) provide a basis for understanding how organizational change can underpin or build organizational resilience.

An extensive literature review has been made to discuss the goals of OC as well as the enablers of OR. A number of conceptual models have been introduced to demonstrate the correlation between OC and OR and the potential role of OC in supporting OR. Empirical findings were also introduced in order to support the theoretical basis of this research.

This study argues that OC can be practiced for the purpose of building or supporting OR. A variety of views have been introduced to demonstrate the correlation between OC and OR and the role of OC in supporting OR.

The purpose and scope of OC should not only be confined to enabling organizations to respond to the dynamics of their business environments but also to enable organizations to withstand a wider range of internal disruptions, major incidents and external factors. This perspective provides a broader insight that is different from the traditional conceptualization of the goals and purpose of OC.

To the author’s knowledge, this is one of very few studies that discuss the correlation between OC and OR and the role of OC in building OR. This explains the need for more practical change initiatives that aim to elevate levels of OR.

Digital technologies create myriad innovation opportunities and have inspired the establishment of many new start-ups in recent years. Despite the growing knowledge on digital entrepreneurship, few studies explore how start-ups exploit these opportunities to achieve entrepreneurial success. The purpose of this paper is to explore start-ups’ capabilities for successful delivery of digital artefacts in a cloud computing infrastructure.

Empirical data were collected during a qualitative case study of an established start-up in the Chinese market by interviewing 41 interviewees. Informed by the notion of dynamic capabilities and using the Gioia methodology, the case firm's life cycle was analysed in detail.

The study identifies start-ups’ ordinary and dynamic capabilities for successful development and delivery of digital services. The findings provide insights into a portfolio of start-ups’ capabilities, namely adaptation, networking, reengineering and refinement.

The study suggests that start-ups’ capabilities and underlying entrepreneurial actions determine the degree to which adoption of digital technologies create and transfer value to customers. The study offers specific insights into how start-ups successfully develop and deliver digital artefacts in a cloud infrastructure based on entrepreneurs' prior expertise, vision and accumulated experience.

This study aims to assess the effectiveness of a scale measuring artificial intelligence capabilities by using the resource-based theory. It seeks to examine the impact of these capabilities on the organizational-level resources of dynamic capabilities and organizational creativity, ultimately influencing the overall performance of government organizations.

The calibration of artificial intelligence capabilities scale was conducted using a combination of qualitative and quantitative analysis tools. A set of 26 initial items was formed in the qualitative study. In the quantitative study, self-reported data obtained from 344 public managers was used for the purposes of refining and validating the scale. Hypothesis testing is carried out to examine the relationship between theoretical constructs for the purpose of nomological testing.

Results provide empirical evidence that the presence of artificial intelligence capabilities positively and significantly impacts dynamic capabilities, organizational creativity and performance. Dynamic capabilities also found to partially mediate artificial intelligence capabilities relationship with organizational creativity and performance, and organizational creativity partially mediates dynamic capabilities – organizational creativity link.

The application of artificial intelligence holds promise for improving decision-making and problem-solving processes, thereby increasing the perceived value of public service. This can be achieved through the implementation of regulatory frameworks that serve as a blueprint for enhancing value and performance.

There are a limited number of studies on artificial intelligence capabilities conducted in the government sector, and these studies often present conflicting and inconclusive findings. Moreover, these studies indicate literature has not adequately explored the significance of organizational-level complementarity resources in facilitating the development of unique capabilities within government organizations. This paper presents a framework that can be used by government organizations to assess their artificial intelligence capabilities-organizational performance relation, drawing on the resource-based theory.

This study aims to examine the enablers of productivity of enterprise-level Agile development process using modified total interpretative structural modeling (TISM). The two main objectives of the current study are to determine the variables influencing enterprise-level agile development productivity and to develop modified TISM for the corresponding components.

To identify enablers of the productivity of enterprise-level agile software development process a literature review and opinions of domain experts were collected. A hierarchical relationship among variables that show direct and indirect influence is created using the modified TISM (M-TISM) technique with Cross Impact Matrix-Multiplication Applied to Classification analysis. This study examined and analyzed the relationships between the determinants within the enterprise using a M-TISM technique.

With the literature review, the study could identify ten enabling factors of the productivity of Agile development process at the enterprise level. Results depict that program increment (PI) planning and scalable backlog management, continuous integration and continuous delivery (CI/CD), agile release trains (ART), agile work culture, delivery excellence, lean and DevOps practices, value stream mapping (VMS), team skills and expertise, collaborative culture, agile coaching, customer engagement have an impact on the productivity of enterprise-level Agile development process. The results show that team collaboration, agile ways of working and customer engagement have a greater impact on productivity improvement for enterprise-level Agile development process.

The developed model is useful for organizations employing scaled Agile development processes in software development. This study provides a recommended listing of key enablers, that may enable productivity improvements in the Agile development process at the enterprise level. Strategists should focus on team collaboration and Agile project management. This study offers a modified TISM model to academicians to help them understand the effects of numerous variables on maintaining the productivity of an enterprise-level Agile. The identified characteristics and their hierarchical structure can help project managers during the execution of Agile projects at the enterprise level, more effectively, increasing their success and productivity.

The study addresses the gap in the literature by interpretative relationships between the identified enabling factors. The model validation is carried out by a panel of nine experts from several information technology organizations deploying Agile software development at the enterprise level. This unique method broadens the knowledge base in Agile software development at scale and provides project managers and practitioners with a practical foundation.

The construction industry has considerably evolved in the recent two decades due to the emergence of sustainability, lean construction (LC) and building information modelling (BIM). Despite previous research efforts, there is still a gap concerning the multidimensional nature of their integration. Hence, this study aims to fill the mentioned knowledge gap through exploring and comparing the challenges, enablers, techniques as well as benefits of integrating LC with BIM and sustainability in building construction projects.

A systematic literature review was conducted to fulfill the purpose of this study.

The findings reveal and compare the challenges, enablers, techniques and benefits of integrating LC with BIM and sustainability in building construction projects. The results suggest that there are eight common challenges for integrating LC with BIM and sustainability, including high initial cost, lack of collaboration, lack of professionals and lack of compatible contractual framework. The discovered challenges, enablers, techniques and benefits seem to be mostly routed in people. The findings also suggest that the synergistic benefits of integrating LC with BIM and sustainability can overcome the common challenges (safety, reliability, productivity, collaboration and quality) in construction projects.

The findings contribute to the literature and practice concerning the integration of LC with BIM and sustainability by exploring, comparing and discussing the relevant challenges, enablers, techniques as well as benefits. Moreover, the findings reveal the significance of the development of people in construction industry, besides processes and technology, as people are always subject of activities in construction while processes and technology are always objects.