Search results

Business Model Innovation is increasingly created by an ecosystem of related companies. This paper aims to investigate the transition of a manufacturing ecosystem toward electric vehicles from a business model perspective.

The authors investigate an automotive manufacturing ecosystem that is in transition toward electric and electrified vehicles, conducting semi-structured interviews with 46 informants from 27 ecosystem members.

The results reveal that the actions of several ecosystem members are driven by regulations relating to emissions. Novel requirements regarding components and complementary offers necessitate the entry of actors from other industries and the formation of new ecosystem members. While the newly emerged ecosystem has roots in an established ecosystem, it relies on new value offers. Further, the findings highlight the importance of ecosystem governance, while the necessary degree of change in the members' business models depends on their roles and positions in the ecosystem. Therefore, upstream suppliers of components must perform business model adaptation, whereas downstream providers must perform more complex business model innovation.

The paper is among the first to investigate an entire manufacturing ecosystem and analyze its transition toward electric vehicles and the implications for business model innovation.

This study aims to address three research questions pertaining to climate neutrality within the supply chain of metal and mining industry: (1) How can an organization implement practices related to climate neutrality in the supply chain? (2) How do members of the supply chain adopt different measures and essential processes to assist an organization in responding to climate change-related concerns? (3) How can the SAP-LAP framework assist in analyzing and proposing solutions to attain climate neutrality?

To address the proposed research questions concerning climate neutrality, this study employs a case study approach utilizing the SAP-LAP (situation, actor, process–learning, action, performance) framework. Within the SAP-LAP framework, adopting a natural resource-based perspective, the study thoroughly examines the intricacies and interactions among existing situations, pertinent actors and processes that impact climate initiatives within a metal and mining company.

The study's findings suggest that organizations can achieve the objective of climate neutrality by prioritizing resources and capabilities that lead to reduced GHG emissions, lower energy consumption and optimal resource utilization. The study further proposes key elements that significantly influence the pursuit of climate neutrality within enterprises.

This study is one of the earliest contributions to the development of a holistic understanding of climate neutrality in the supply chain of the metal and mining industry.

The study will assist practitioners and policymakers in comprehending the present circumstances, actors and processes involved in enterprises' supply networks in order to attain climate neutrality in supply chains, as well as in taking the right steps to enhance performance.

This study presents a climate neutrality model and provides valuable insights into emission management, contributing to the achievement of the climate neutrality objective.

In an increasingly interconnected world, transportation infrastructure has emerged as a critical determinant of economic growth and global competitiveness. High-speed rail (HSR), characterized by its exceptional speed and efficiency, has garnered widespread attention as a transformative mode of transportation that transcends borders and fosters economic development. The Kuala Lumpur – Singapore (KL-SG) HSR project stands as a prominent exemplar of this paradigm, symbolizing the potential of HSR to serve as a catalyst for national economic advancement.

This paper is prepared to provide an insight into the benefits and advantages of HSR based on proven case studies and references from global HSRs, including China, Spain, France and Japan.

The findings that have been obtained focus on enhanced connectivity and accessibility, attracting foreign direct investment, revitalizing regional economies, urban development and city regeneration, boosting tourism and cultural exchange, human capital development, regional integration and environmental and sustainability benefits.

The KL-SG HSR, linking Kuala Lumpur and Singapore, epitomizes the potential for HSR to be a transformative agent in the realm of economic development. This project encapsulates the aspirations of two dynamic Southeast Asian economies, united in their pursuit of sustainable growth, enhanced connectivity and global competitiveness. By scrutinizing the KL-SG High-Speed Rail through the lens of economic benchmarking, a deeper understanding emerges of how such projects can drive progress in areas such as cross-border trade, tourism, urban development and technological innovation.

The present paper aims to address challenges associated with path planning and obstacle avoidance in mobile robotics. It introduces a pioneering solution called the Bi-directional Adaptive Enhanced A* (BAEA*) algorithm, which uses a new bidirectional search strategy. This approach facilitates simultaneous exploration from both the starting and target nodes and improves the efficiency and effectiveness of the algorithm in navigation environments. By using the heuristic knowledge A*, the algorithm avoids unproductive blind exploration, helps to obtain more efficient data for identifying optimal solutions. The simulation results demonstrate the superior performance of the BAEA* algorithm in achieving rapid convergence towards an optimal action strategy compared to existing methods.

The paper adopts a careful design focusing on the development and evaluation of the BAEA* for mobile robot path planning, based on the reference [18]. The algorithm has remarkable adaptability to dynamically changing environments and ensures robust navigation in the context of environmental changes. Its scale further enhances its applicability in large and complex environments, which means it has flexibility for various practical applications. The rigorous evaluation of our proposed BAEA* algorithm with the Bidirectional adaptive A* (BAA*) algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm. The BAEA* algorithm consistently outperforms BAA*, demonstrating its ability to plan shorter and more stable paths and achieve higher success rates in all environments.

The paper adopts a careful design focusing on the development and evaluation of the BAEA* for mobile robot path planning, based on the reference [18]. The algorithm has remarkable adaptability to dynamically changing environments and ensures robust navigation in the context of environmental changes. Its scale further enhances its applicability in large and complex environments, which means it has flexibility for various practical applications. The rigorous evaluation of our proposed BAEA* algorithm with the Bi-directional adaptive A* (BAA*) algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm.

The rigorous evaluation of our proposed BAEA* algorithm with the BAA* algorithm [18] in five different environments demonstrates the superiority of the BAEA* algorithm. The BAEA* algorithm consistently outperforms BAA*, demonstrating its ability to plan shorter and more stable paths and achieve higher success rates in all environments.

The originality of this paper lies in the introduction of the bidirectional adaptive enhancing A* algorithm (BAEA*) as a novel solution for path planning for mobile robots. This algorithm is characterized by its unique characteristics that distinguish it from others in this field. First, BAEA* uses a unique bidirectional search strategy, allowing to explore the same path from both the initial node and the target node. This approach significantly improves efficiency by quickly converging to the best paths and using A* heuristic knowledge. In particular, the algorithm shows remarkable capabilities to quickly recognize shorter and more stable paths while ensuring higher success rates, which is an important feature for time-sensitive applications. In addition, BAEA* shows adaptability and robustness in dynamically changing environments, not only avoiding obstacles but also respecting various constraints, ensuring safe path selection. Its scale further increases its versatility by seamlessly applying it to extensive and complex environments, making it a versatile solution for a wide range of practical applications. The rigorous assessment against established algorithms such as BAA* consistently shows the superior performance of BAEA* in planning shorter paths, achieving higher success rates in different environments and cementing its importance in complex and challenging environments. This originality marks BAEA* as a pioneering contribution, increasing the efficiency, adaptability and applicability of mobile robot path planning methods.

The study examines the social and environmental responsibility indicators disclosed by three International Council on Mining and Metals (ICMM) corporate mining members in their social and environmental reporting (SER) from 2006 to 2014. To achieve this aim, the author limits the data two years before (i.e. from 2006 to 2007) and six years after (i.e. from 2009 to 2014) the implementation of the Sustainable Development Framework in the mining sector in 2008.

Using the techniques of content analysis and interpretive textual analysis, this study examines 27 social and environmental responsibility reports published between 2006 and 2014 by three ICMM corporate mining members. The study develops a disclosure index based on the earlier work of Hackston and Milne (1996), together with other disclosure items suggested in the extant literature and considered appropriate for this work. The disclosure index for this study comprised six disclosure categories (“employee”, “environment”, “community involvement”, “energy”, “governance” and “general”). In each of the six disclosure categories, only 10 disclosure items were chosen and that results in 60 disclosure items.

A total of 830 out of a maximum of 1,620 social and environmental responsibility indicators, representing 51% (168 employees, 151 environmental, 145 community involvement, 128 energy, 127 governance and 111 general) were identified and examined in company SER. The study showed that the sample companies relied on multiple strategies for managing pragmatic legitimacy and moral legitimacy via disclosures. Such practices raise questions regarding company-specific disclosure policies and their possible links to the quality/quantity of their disclosures. The findings suggest that managers of mining companies may opt for “cherry-picking” and/or capitalise on events for reporting purposes as well as refocus on company-specific issues of priority in their disclosures. While such practices may appear appropriate and/or timely to meet stakeholders’ needs and interests, they may work against the development of comprehensive reports due to the multiple strategies adopted to manage pragmatic and moral legitimacy.

A limitation of this research is that the author relied on self-reported corporate disclosures, as opposed to verifying the activities associated with the claims by the sample mining companies.

The findings from this research will help future social and environmental accounting researchers to operationalise Suchman’s typology of legitimacy in other contexts.

With growing large-scale mining activity, potential social and environmental footprints are obviously far from being socially acceptable. Powerful and legitimacy-conferring stakeholders are likely to disapprove such mining activity and reconsider their support, which may threaten the survival of the mining company and also create a legitimacy threat for the whole mining industry.

This study innovates by focusing on Suchman’s (1995) typology of legitimacy framework to interpret SER in an industry characterised by potential social and environmental footprints – the mining industry.

This paper presents a new and well-structured framework that aims to assess the current environmental impact from a Greenhouse Gas (GHG) emissions perspective. This tool includes a new set of Lean Key Performance Indicators (KPIs), which translates the well-known logic of Overall Equipment Effectiveness in the field of GHG emissions, that can progressively detect industrial losses that cause GHG emissions and support decision-making for implementing improvements.

The new metrics are presented with reference to two different perspectives: (1) to highlight the deviation of the current value of emissions from the target; (2) to adopt a diagnostic orientation not only to provide an assessment of current performance but also to search for the main causes of inefficiencies and to direct improvement implementations.

The proposed framework was applied to a major company operating in the plywood production sector. It identified emission-related losses at each stage of the production process, providing an overall performance evaluation of 53.1%. The industrial application shows how the indicators work in practice, and the framework as a whole, to assess GHG emissions related to industrial losses and to proper address improvement actions.

This paper scrutinizes a new set of Lean KPIs to assess the industrial losses causing GHG emissions and identifies some significant drawbacks. Then it proposes a new structure of losses and KPIs that not only quantify efficiency but also allow to identify viable countermeasures.

Prior research has extensively examined how bringing technology from work into the non-work life domain creates conflict, yet the reverse pathway has rarely been studied. The purpose of this study is to bridge this gap and examine how the non-work use of smartphones in the workplace affects work–life conflict.

Drawing from three literature streams: technostress, work–life conflict and role boundary theory, the authors theorise on how limiting employees' ability to integrate the personal life domain into work, by means of technology use policy, contributes to stress and work–life conflict. To test this model, the authors employ a natural experiment in a company that changed its policy from fully restricting to open smartphone access for non-work purposes in the workplace. The insights gained from the experiment were explored further through qualitative interviews.

Work–life conflict declines when a ban on using smartphones for non-work purposes in the workplace is revoked. This study's results show that the relationship between smartphone use in the workplace and work–life conflict is mediated by sensed stress. Additionally, a post-hoc analysis reveals that work performance was unchanged when the smartphone ban was revoked.

First, this study advances the authors' understanding of how smartphone use policies in the workplace spill over to affect non-work life. Second, this work contributes to the technostress literature by revealing how, in specific situations, engagement with ICT can reduce distress and strain.

The purpose of this study is to shed light on the twin transition in China in the organization of innovation processes in artificial intelligence (AI) and green technology (GT) development and to understand the role of foreign multinationals in Chinese innovation systems.

A qualitative research approach is used by interviewing executives from German multinationals with expertise in AI and GT development and organization of innovation processes in China. In total, 11 semi-structured interviews were conducted with companies, and the data were analysed with a thematic qualitative text analysis.

The findings show that AI applications for GT are primarily developed in cross-company projects that are led by local and regional authorities through the organization of industrial districts and clusters. German multinationals are either being integrated, remaining autonomous or being excluded from these twin transition innovation processes.

This paper aims to fill the gap in the literature by providing one of the first qualitative approach towards twin transition innovation processes in China and exploring the integration of multinational enterprises in cluster organizations. To the best of the author’s knowledge, this is one of the first twin transition studies from this perspective in emerging economies.

The service environment is becoming increasingly turbulent, leading to calls for a systemic understanding of it as a set of dynamic service ecosystems. This paper advances this understanding by developing a typology of service ecosystem dynamics that explains the varying interplay between change and stability within the service environment through distinct behavioral patterns exhibited by service ecosystems over time.

This study builds upon a systematic literature review of service ecosystems literature and uses system dynamics as a method theory to abductively analyze extant literature and develop a typology of service ecosystem dynamics.

The paper identifies three types of service ecosystem dynamics—behavioral patterns of service ecosystems—and explains how they unfold through self-adjustment processes and changes within different systemic leverage points. The typology of service ecosystem dynamics consists of (1) reproduction (i.e. stable behavioral pattern), (2) reconfiguration (i.e. unstable behavioral pattern) and (3) transition (i.e. disrupting, shifting behavioral pattern).

The typology enables practitioners to gain a deeper understanding of their service environment by discerning the behavioral patterns exhibited by the constituent service ecosystems. This, in turn, supports them in devising more effective strategies for navigating through it.

The paper provides a precise definition of service ecosystem dynamics and shows how the identified three types of dynamics can be used as a lens to empirically examine change and stability in the service environment. It also offers a set of research directions for tackling service research challenges.