Search results

Just transition is a fundamental concept for supply chain management but neither discipline pays attention to the other and little is known about how supply chains can be orchestrated as socioecological systems to manage these transitions. Building from a wide range of just transition examples, this paper explores just transition to understand how to move beyond instrumental supply chain practices to supply chains functioning in harmony with the planet and its people.

Building from a systematic review of 72 papers, the paper identifies just transition examples while interpreting them through the theoretical lens of supply chain management, providing valuable insights to help research and practice understand how to achieve low-carbon economies through supply chain management in environmentally and socially just ways.

The paper defines, elaborates, and extends the just transition construct by developing a transition taxonomy with two key dimensions. The purpose dimension (profit or shared outcomes) and the governance dimension (government-/industry-led versus civil society-involved), generating four transition archetypes. Most transitions projects are framed around the Euro- and US-centric, capitalist standards of development, leading to coloniality as well as economic and cultural depletion of communities. Framing just transition in accordance with context-specific plural values, the paper provides an alternative perspective to the extractive transition concept. This can guide supply chain management to decarbonise economies and societies by considering the rights of nature, communities and individuals.

Introducing just transition into the supply chain management domain, this paper unifies the various conceptualisations of just transition into a holistic understanding, providing a new foundation for supply chain management research.

Further investigation is needed of network effectiveness in healthcare and how it is influenced by unpredictable events like COVID-19. Based on Provan and Milward’s (2001) framework, this study investigates the effectiveness criteria of healthcare networks and their potential contribution to network effectiveness during the pandemic’s challenges.

This research employs an explanatory case study in a local area of Italy’s Lombardy Region and analyzes network effectiveness at the network level based on network member perceptions.

Network effectiveness refers to the network’s ability to address patient needs, guaranteeing services through network members' coordinated efforts and a central coordinator that facilitates their interaction. Members’ capacity to strengthen their roles played a crucial part in sustaining network effectiveness when COVID-19 revised other members’ priorities and threatened achievement of network goals.

This study’s findings equip healthcare managers and policymakers with knowledge about network effectiveness criteria at the network level, offering suggestions for managerial practices and network design to address exogenous shocks.

This study identifies factors that influence network effectiveness criteria and provides insight into how network members can contribute to sustaining effectiveness during crises.

The purpose of this study is to revisit the conventional wisdom about a key contribution [i.e. strengths, weaknesses, opportunities, threats (SWOT) analysis] in the field of strategic management. The societal context and the role of academics, consultants and executives is taken into account in the emergence of SWOT analysis during the 1960–1980 period as a pivotal development within the broader context of the satisfactory, opportunities, faults, threats (SOFT) approach. The authors report on both the content and the approach, so that other scholars seeking to invigorate indigenous theories and/or underreported strategy practices will thrive.

Applying a historiographic approach, the authors introduce an evidence-based methodology for interpreting historical sources. This methodology incorporates source criticism, triangulation and hermeneutical interpretation, drawing upon insights from robust evidence through three iterative stages.

The underreporting of the SOFT approach/SWOT analysis can be attributed to several factors, including strategy tools being integrated into planning frameworks rather than being published as standalone materials; restricted circulation of crucial long-range planning service/theory and practice of planning reports due to copyright limitations; restricted access to the Stanford Research Institute Planning Library in California; and the enduring popularity of SOFT and SWOT variations, driven in part by their memorable acronyms.

In the spirit of a renaissance in strategic planning research, the authors unveil novel theoretical and social connections in the emergence of SWOT analysis by combining evidence from both theory and practice and delving into previously unexplored areas.

Caution is advised for scholars who examine the discrete time frame of 1960–1980 through mere bibliometric techniques. This study underscores the risks associated with gathering incomplete and/or inaccurate data, emphasizing the importance of triangulating evidence beyond scholarly databases. The paradigm shift of strategic management research due to the advent of large language models poses new challenges and the risk of conserving and perpetuating academic urban legends, myths and lies if training data is not adequately curated.

This study aims to quantify and analyse the dynamics of land use and land cover (LULC) changes over three decades in the rapidly urbanizing city of Abha, Saudi Arabia, and to assess urban growth using Morphological Spatial Pattern Analysis (MSPA).

Using the Support Vector Machine (SVM) classification in Google Earth Engine, changes in land use in Abha between 1990 and 2020 are accurately assessed. This method leverages cloud computing to enhance the efficiency and accuracy of big data analysis. Additionally, MSPA was employed in Google Colab to analyse urban growth patterns.

The study demonstrates significant expansion of urban areas in Abha, growing from 62.46 km² in 1990 to 271.45 km² in 2020, while aquatic habitats decreased from 1.36 km² to 0.52 km². MSPA revealed a notable increase in urban core areas from 41.66 km² in 2001 to 194.97 km² in 2021, showcasing the nuanced dynamics of urban sprawl and densification.

The novelty of this study lies in its integrated approach, combining LULC and MSPA analyses within a cloud computing framework to capture the dynamics of city and environment. The insights from this study are poised to influence policy and planning decisions, particularly in fostering sustainable urban environments that accommodate growth while preserving natural habitats. This approach is crucial for devising strategies that can adapt to and mitigate the environmental impacts of urban expansion.

Authorities have set up numerous security checkpoints during times of armed conflict to control the flow of commercial and humanitarian trucks into and out of areas of conflict. These security checkpoints have become highly utilized because of the complex security procedures and increased truck traffic, which significantly slow the delivery of relief aid. This paper aims to improve the process at security checkpoints by redesigning the current process to reduce processing time and relieve congestion at checkpoint entrance gates.

A decision-support tool (clearing function distribution model [CFDM]) is used to minimize the effects of security checkpoint congestion on the entire humanitarian supply network using a hybrid simulation-optimization approach. By using a business process simulation, the current and reengineered processes are both simulated, and the simulation output was used to estimate the clearing function (capacity as a function of the workload). For both the AS-IS and TO-BE models, key performance indicators such as distribution costs, backordering and process cycle time were used to compare the results of the CFDM tool. For this, the Kerem Abu Salem security checkpoint south of Gaza was used as a case study.

The comparison results demonstrate that the CFDM tool performs better when the output of the TO-BE clearing function is used.

The efforts will contribute to improving the planning of any humanitarian network experiencing congestion at security checkpoints by minimizing the impact of congestion on the delivery lead time of relief aid to the final destination.

This paper demystifies the fluid workforce phenomenon increasingly discussed in the circles of organizational innovators and explores the characteristic aspects of the fluid workforce in the healthcare sector.

We analyze the concept and provide a generic review of definitions of a fluid workforce in relation to other similar concepts established in the academic and practitioner literature, contextualize the fluid workforce phenomenon in healthcare and distinguish relevant drivers and categories of fluid workers in this sector. We also discuss the implications of a fluid workforce for healthcare organizations, drawing on the health labor market and human resource management (HRM) practices frameworks.

The fluid workforce in healthcare is not new. Today’s main novelties are related to the wide diversity of types of fluid workforce that have emerged, the expanding scale of diffusion of the fluid workforce and the emergence of digital technologies to support HRM decisions. While a fluid workforce may provide solutions to address mismatches in the supply and demand of health workers, it can also worsen working conditions, increase dual practice and have implications for existing HRM practices.

We disentangle a novel term for the public sector, healthcare and HRM literature. We discern similarities and distinctions, presenting a framework for managing and analyzing this workforce at organizational and labor market levels in the healthcare sector. Acknowledging the challenges in estimating the existing fluid workforce labor market size, we offer practical methodologies to empirically estimate its prevalence within the healthcare industry and build an agenda for future research.

Supply chains need to be made viable in this volatile and competitive market, which could be possible through digitalization. This study is an attempt to explore the role of Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business performance from the lens of natural resource-based view.

The study tests the proposed model using a covariance-based structural equation modelling and further investigates the ranking of each construct using the artificial neural networks approach in AMOS and SPSS respectively. A total of 234 respondents selected using purposive sampling aided in capturing the industry practices across supply chains in the UK. The full collinearity test was carried out to study the common method bias and the content validity was carried out using the item content validity index and scale content validity index. The convergent and discriminant validity of the constructs and mediation study was carried out in SPSS and AMOS V.23.

The results are overtly inferring the significant impact of Industry 4.0 practices on creating smart and ultimately sustainable supply chains. A partial relationship is established between Industry 4.0 and supply chain agility through a smart supply chain. This work empirically reinstates the combined significance of green practices, Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business value. The study also uses the ANN approach to determine the relative importance of each significant variable found in SEM analysis. ANN determines the ranking among the significant variables, i.e. supply chain resilience > green practices > Industry 4.0> smart supply chain > supply chain agility presented in descending order.

This study is a novel attempt to establish the role of digitalization in SCs for attaining sustainable business value, providing empirical support to the mediating role of supply chain agility, supply chain resilience and smart supply chain and manifests a significant integrated framework. This work reinforces the integrated model that combines all the constructs dealt with in silos so far in prior literature.

The purpose of this action research study was to design, implement and evaluate interventions that enhanced the induction program for new teachers in a P-12 school district. At the outset, we hoped the study would provide new teacher support resulting in improved teaching practices, increased job satisfaction and/or increased teacher retention among the target population. With this in mind, our research question was: What structures and supports from a school-university partnership facilitate capacity-building among university teacher education faculty, school and district leaders, mentor teachers, and new teachers in the context of an induction program?

This study used an intervention-centered mode of action research methodology that aims to make systems-level change. This type of action research intends to solve real organizational problems with a focus on conducting “research in action” rather than “research about action” (Coghlan and Brannick, 2014, pp. 5–6). This approach necessitates that data collection and analysis are iterative processes, occurring throughout the research process, instead of solely at the end stages of the research process. Our action research process used Coghlan and Brannick’s (2014) action research cycle model. The cyclical four-step process includes constructing (verifying the problem in the local context), planning action, taking action and evaluating action. Facilitated by the interim director of a Professional development schools (PDS) partnership in the Southeastern United States, a team of co-researchers which included three university teacher education faculty and four school district administrators used action research methodology to create systemic change that enhanced the district’s induction program. We collected data through multiple qualitative methods, including surveys, focus groups, observations and interviews during the course of three action research cycles. These data and our theoretical framework (complex adaptive systems theory and social network theory) informed two major interventions that supported new teachers during the challenging first year of the coronavirus disease (COVID-19) pandemic.

The interventions and the research process were mutually beneficial for both institutions and contributed to professional learning and growth at the individual, group and system levels. The three major findings described include: (1) engaging in collaborative action research is mutually beneficial for both schools and universities; (2) induction programs benefit from university resources; (3) learning communities build all educators’ professional capacity.

Our research recommendations are: (1) more research is needed on the benefits of school-university partnerships to induction programs; (2) school-university partnerships should leverage action research to improve systems; (3) within school-university partnerships, the connection between collaborative leadership and sustainability requires further research. One limitation was that this study was conducted in a single school-university partnership context involving a large public university and a mid-sized public school district that had a well-established partnership. More induction-centered research is needed in different types of school-university partnership contexts that have varying levels of longevity and partnership structures.

Our recommendations for practice include (1) school-university partnerships should leverage collaborative learning communities to catalyze individual, group and systems-level learning and change, and (2) school-university partnerships must prioritize induction support to strengthen the teaching profession.

Since Hunt’s (2014) literature review on induction support in PDS partnerships, very few empirical studies have been conducted in this research area. This study, which examined induction support in a PDS partnership over a two-year period, makes a significant contribution to the scholarly literature on induction teacher support in school-university partnership contexts. Facilitated by the interim director of a PDS partnership, a team of co-researchers, which included three university teacher education faculty and four school district administrators, used action research methodology to create systems-level supports that enhanced the district’s induction program.

Several studies have shown that economic shock and crisis trigger companies to move forward innovatively. This paper aims to compliment this research topic by investigating how SMEs activate their organization resilience to adapt to changes generated by a crisis, with specific focus on how digitalization is used as an opportunity on this road. COVID-19 pandemic provided the context to investigate this situation.

The research approach combines literature review, quantitative data survey and data analysis and modeling using PLS-SEM. The quantitative data survey provided the database for building the structural equation model, exploring the structural relationships between the constructs and testing the hypotheses. Expert discussions contributed to the validation and interpretation of the results.

The model reveals that while organizational resilience has no direct effect on digitalization, combined with available resources, it realizes its indirect impact. Resilient companies require less external financial support to achieve their digitalization goals. The results also confirm that an uncertain environment encourages SMEs to go digital.

Several research studies highlighted the importance of SMEs in recovery from crises. Knowing more about how they can be supported and what capabilities they should develop is essential. This research explores the relationship between organizational resilience, resource availability and digitalization for SMEs in crises like the COVID-19 pandemic, revealing the self-reinforcing effect of organizational resilience and the level of digitalization that was not previously studied.

Preservice teacher (PST) professional development programs are crucial for cultivating high-quality STEAM teachers of the future, significantly impacting the quality of regional STEAM education. The Guangdong-Hong Kong-Macao Greater Bay Area, as a region of cross-border cooperation, integrates the resources and advantages of Guangdong, Hong Kong, and Macao, possessing rich cultural heritage and innovative capabilities. Transdisciplinary Education for Cultural Inheritance (C-STEAM) is an effective approach to promoting educational collaboration within the Greater Bay Area, facilitating the integration of both technological and humanities education. This study aims to develop a Technology-Enabled University-School-Enterprise (T-USE) collaborative education model and implement it in the Greater Bay Area, to explore its role as a support mechanism in professional development and its impact on C-STEAM PSTs' professional capital.

Adopting a qualitative methodology, the study interviewed PSTs who participated in a C-STEAM teacher education course under the T-USE model. Thematic coding is used to analyze their knowledge acquisition, interaction benefits with community members, and autonomous thinking and decision-making in theoretical learning and teaching practice.

The findings show that the T-USE model significantly enhanced the PSTs' human capital, including teaching beliefs, knowledge, and skills. In terms of social capital, PSTs benefited from collaboration with PST groups, university teaching teams, in-service teachers, and enterprises, though challenges such as varying levels of expertise among in-service teachers and occasional technical instability emerged. For decisional capital, the T-USE model provided opportunities for autonomous thinking and promoted teaching judgment skills through real teaching challenges and scenarios. Reflective practice activities also supported PSTs' professional growth.

This study reveals the effectiveness and internal mechanism of the T-USE model in C-STEAM PST training, offering significant theoretical and practical references for future PST education.