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This study aims to analyze how startups organize their purchasing activities to improve operative excellence and become attractive customers.

The authors use a two-phase exploratory approach with semistructured interviews and a World Café. In total, 20 startup purchasers and suppliers participated. It is an international study with participants from eight countries (Belgium, Brazil, France, Germany, Hungary, The Netherlands, the UK and the USA).

The authors find that startups organize the purchasing function in five ways: partial outsourcing, transactional-oriented, strategic only, outsourced purchasing and full department. Each type has advantages and disadvantages regarding operative excellence. The authors identify type-specific antecedents to operative excellence: forecasting, payment habits, ordering process, contact accessibility and quick decision-making.

The value of this paper is that it offers entrepreneurs a framework to organize startup purchasing activities, including outsourcing options. Furthermore, it provides theoretical contributions that expand the topic of purchasing and supply organization and operative excellence to the startup context.

The value of this paper is that, to the best of the authors’ knowledge, it is the first to explore purchasing organization and operative excellence in startups.

Digital labor platforms (DLPs) are transforming the nature of the work for an increasing number of workers, especially through extensively employing automated algorithms for performing managerial functions. In this novel working setting – characterized by algorithmic governance, and automatic matching, rewarding and punishing mechanisms – gig-workers play an essential role in providing on-demand services for final customers. Since gig-workers’ continued participation is crucial for sustainable service delivery in platform contexts, this study aims to identify and examine the antecedents of their working outcomes, including burnout and engagement.

We suggested a theoretical framework, grounded in the job demands-resources heuristic model to investigate how the interplay of job demands and resources, resulting from working in DLPs, explains gig-workers’ engagement and burnout. We further empirically tested the proposed model to understand how DLPs' working conditions, in particular their algorithmic management, impact gig-working outcomes.

Our findings indicate that job resources – algorithmic compensation, work autonomy and information sharing– have significant positive effects on gig-workers’ engagement. Furthermore, our results demonstrate that job insecurity, unsupportive algorithmic interaction (UAI) and algorithmic injustice significantly contribute to gig-workers’ burnout. Notably, we found that job resources substantially, but differently, moderate the relationship between job demands and gig-workers’ burnout.

This study contributes a theoretically accurate and empirically grounded understanding of two clusters of conditions – job demands and resources– as a result of algorithmic management practice in DLPs. We developed nuanced insights into how such conditions are evaluated by gig-workers and shape their engagement or burnout in DLP emerging work settings. We further uncovered that in gig-working context, resources do not similarly buffer against the negative effects of job demands.

Of critical concern to the world is the need to reduce consumption and waste of natural resources. This study provides a multi-level exploration of the ways situational and transformational links between levels and challenges are related to the adoption and utilization of material flow cost accounting in Vietnam, to encourage green productivity.

Based on triangulation of public documents at different institutional levels and a set of semi-structured interviews, situational and transformational links and challenges for material flow cost accounting in Vietnam are examined using purposive and snowball sampling of key actors.

Using a multi-level framework the research identifies six situational and transformational barriers to implementation of material flow cost accounting and suggests opportunities to overcome these. The weakest links identified involve macro-to meso-situational and micro-to macro-transformational links. The paper highlights the dominance of meso-level institutions and lack of focus on micro transformation to cut waste and enable improvements in green productivity.

The paper identifies ways for companies in Vietnam to reduce unsustainability and enable transformation towards sustainable management and waste reduction.

The paper is the first to develop and use a multi-level/multi-time period framework to examine the take-up of material flow cost accounting to encourage transformation towards green productivity. Consideration of the Vietnamese case builds understanding of the challenges for achieving United Nations Sustainable Development Goal number 12, to help enable sustainable production and consumption patterns.

The purpose of the article is to contribute to the body of research on digital transformation among members of the supply chain operating in an emerging economy. This paper researches the digital transformation trends happening across Vietnamese supply chains, by investigating the current adoption rates, predicted impact levels and financial investments being made in key Industry 4.0 technologies.

By using a semi-structured online survey, the experiences of 281 supply chain professionals in Vietnam were captured. Subsequently, statistical techniques examining variances in means, regression analysis and Monte Carlo simulation were applied.

The findings of this study offer a comprehensive understanding of Industry 4.0 technology in Vietnam, highlighting the prevalent technologies being prioritized. Big data analytics and the Internet of things are expected to have the most substantial impact on businesses over the next 5–10 years and have received the most financial investment. Conversely, Blockchain is perceived as having less potential for future investment. The study further identifies several technological synergies, such as combining advanced robotics, artificial intelligence and the Internet of things to build effective and flexible factories, that can lead to more comprehensive solutions. It also extends diffusion of innovation theory, encompassing investment and impact considerations.

This study offers valuable insights into the impact and financial investment in Industry 4.0 technologies by Vietnamese supply chain firms. It provides a theoretical contribution via an extension of the diffusion of innovation theory and contributes toward a better understanding of the current Industry 4.0 landscape in developing economies. The findings have significant implications for future managerial decision-making, on the impact, viability and resourcing needs when undertaking digital transformation.

The purpose of this paper is to give an overview of existing literature on post-traumatic growth (PTG), particularly in the ways that it relates to grief.

This narrative literature review brings together 125 sources and presents them in a readable way.

There is a great deal of evidence to suggest that PTG can come from grief. This is not always the case, however.

This review presents only a selection of the existing literature – the review is not systematic. However, this allows for a narrative to be crafted, to aid readability.

Suggestions for future research are made throughout, and potential therapeutic applications are mentioned.

This paper discusses stigma, in the form of “disenfranchised grief”. In this, social pressures and expectations affect how a person processes their grief psychologically. While movements to increase discourse and reduce stigma are on the rise, more is needed.

This review guides readers through existing literature, providing a wide overview of the topic of PTG in grief.

Digital transformation is crucial for achieving high-quality development in the construction industry. Assessing the industry's digital maturity is an urgent necessity. The Digital Transformation Maturity Model is a potential tool to systematically evaluate the digital maturity levels of various industries. However, most existing models predominantly focus on sectors such as the Internet and manufacturing, leaving the construction industry comparatively underrepresented. This study aims to address this gap by developing a maturity model tailored specifically for digital transformation within the construction industry.

This study leverages the Capability Maturity Theory and integrates the unique characteristics of the construction industry to construct a comprehensive maturity model for digital transformation. The model comprises five critical dimensions: industry environment, strategy and organization, digital infrastructure, business process and management digitization, and digital performance. These dimensions encompass a total of 25 assessment indexes. To validate the model's feasibility and effectiveness, a digital transformation maturity assessment was conducted within China's construction industry.

The results of the maturity assessment within the Chinese construction industry reveal that it currently operates at the third level of digital maturity (defined level). The industry's maturity score stands at 2.329 out of 5. This outcome indicates that the developed model is accurate and reliable in assessing the level of digital transformation maturity within the construction industry.

This paper contributes both practical and theoretical insights to the field of digital transformation within the construction industry. By creating a tailored maturity model, it addresses a significant gap in existing research and offers a valuable tool for assessing and advancing digital maturity levels within this industry.

Sustainable construction deficits are common in developing economies, and resolutions are constrained by the failure to prioritise the plethora of available indicators. This study aims to report on overlapping indicators for benchmarking sustainable construction for construction organisations.

Online survey data were collected from construction professionals, academics and senior managers in government bodies. Pearson chi-squared tests and overlapping analysis were used to determine significant indicators. Kruskal–Wallis tests were used to determine statistically significant differences among the dimensions.

Overlapping analysis determined indicators significant for economic, environmental and social performance. Environmental protection and reporting (pollution and emissions) were significant for all three performance dimensions. The most significant indicators are economic performance (adequate competence of key project staff), environmental performance (environmental protection and reporting – pollution and emissions) and social performance (adequate sustainability expenditure by construction organisations). Significant differences due to dimensions existed for adequate competence of key project staff, sustainable construction and eco-design, adequate governance and organisational excellence of construction projects and satisfactory workers’ morale.

Determining overlapping indicators enables prioritised implementation that ensures sustainable construction. Excluding construction workers was a significant limitation for a holistic interrogation.

To the best of the authors’ knowledge, this is the first study to determine overlapping indicators for sustainable construction performance in Zimbabwe.

Demand forecasts are a key component of planning efforts and are crucial for managing core operations. This study aims to evaluate the use of several machine learning (ML) algorithms to forecast demand for residential construction in Jordan.

The identification and selection of variables and ML algorithms that are related to the demand for residential construction are indicated using a literature review. Feature selection was done by using a stepwise backward elimination. The developed algorithm’s accuracy has been demonstrated by comparing the ML predictions with real residual values and compared based on the coefficient of determination.

Nine economic indicators were selected to develop the demand models. Elastic-Net showed the highest accuracy of (0.838) versus artificial neural networkwith an accuracy of (0.727), followed by Eureqa with an accuracy of (0.715) and the Extra Trees with an accuracy of (0.703). According to the results of the best-performing model forecast, Jordan’s 2023 first-quarter demand for residential construction is anticipated to rise by 11.5% from the same quarter of the year 2022.

The results of this study extend to the existing body of knowledge through the identification of the most influential variables in the Jordanian residential construction industry. In addition, the models developed will enable users in the fields of construction engineering to make reliable demand forecasts while also assisting in effective financial decision-making.

With the change in climate and increased pollution, there has been a need to reduce environmental carbon emissions. This research aims to develop a framework for reducing environmental carbon footprints to improve business performance.

This study uses Scientific Procedures and Rationales for the Systematic Literature Reviews (SPAR-4-SLR) approach. Articles are searched in the Scopus database using various keywords and their combinations. It resulted in 651 articles initially. After applying different screening criteria, 61 articles were considered for the final study.

This study provided four themes and sub-themes within each category. This research also used theories, methodologies and context (TMC) framework to provide future research questions. This study used the antecedents, decisions and outcomes (ADO) framework for synthesising the findings. The ADO framework will help to achieve carbon neutrality and improve firms' supply chain (SC) performance.

This study provides theoretical implications by highlighting the various theories that can be used in future research. This study also states the practical implications for the achievement of carbon neutrality by the firms.

This study contributes to the literature linking carbon neutrality with business performance.

A global crisis like that caused by the COVID-19 pandemic threatens the survival of any business, but especially of nascent entrepreneurs, due to their vulnerable situation. At this stage of entrepreneurship, information and communication technology capabilities (ICTCs) are critical skills that help entrepreneurs develop their new businesses, fostering economic adaptability to counteract adverse effects. This study advances knowledge of how nascent entrepreneurs react in an environment of global crisis.

The study analyzes a sample of 331 Spanish nascent entrepreneurs to determine the mediating effect of ICTCs on the relationship between the impact of a global crisis (e.g. COVID-19) and the firm’s strategic response.

The results suggest that crises influence adaptation and compensation strategies significantly and that ICTCs exert a total mediating effect on this relationship. The results do not, however, establish a clear relationship between the impact of the COVID-19 crisis and disengagement response, but rather a negative relationship, possibly influenced by government attempts to mitigate the pandemic’s economic consequences (economic aid to maintain the workforce, financial support for business model survival).

The COVID-19 crisis revealed ICT as a key technology for continuing business operations. This study analyzes how ICTCs affect nascent entrepreneurs’ strategies in crisis environments. Our analysis is important because these entrepreneurs have invested resources in their new project. We must determine their strategic response to crisis environments: adaptation, compensation or disengagement. The sample itself, collected during the pandemic, provides unique insights into the impact of the crisis on nascent business decisions.

像2019冠狀病毒病大流行等的全球危機一旦發生，各工商企業能否繼續生存必會受到威脅和影響。這影響以剛開始發展的創業者為甚，因為他們處於脆弱的處境。在這個創業階段，創業者必須擁有資訊與通訊科技能力，才能發展他們的新業務，他們亦需培養經濟上的適應能力，以能抵銷各種不利的影響。本研究擬就剛開始發展的創業者在全球危機發生時應如何應對進行探討，以增進我們對這課題的知識。

本研究分析一個涵蓋331名西班牙新生創業者的樣本，來鑒定資訊與通訊科技能力對全球危機 (如2019冠狀病毒病) 帶來的影響與企業戰略應對之間的關聯所起的中介效應。

研究結果似顯示，危機會顯著地影響企業的適應和賠償策略; 研究結果似乎也顯示，資訊與通訊科技能力會對這關聯 (全球危機所帶來的影響與企業戰略應對之間的關聯) 發揮極大的中介效應。但研究結果並沒有就2019冠狀病毒病危機的影響與脫離反應、建立明確的關聯。反之，研究結果似顯示兩者有一個負相關的關係，這可能是因為政府施行應對方法，以減輕大流行所帶來的經濟後果所致 (這些應對方法包括用以維持勞動力隊伍的經濟援助、和使商業模式能繼續生存的財政支援) 。

2019冠狀病毒病危機揭示了資訊與通訊科技是讓商業運作能繼續進行的關鍵技術。本研究分析資訊與通訊科技能力如何於危機發生時影響新生創業者的策略。我們的分析有其重要性，這是因為這些創業者把資源投入他們的新項目; 我們必須鑒定他們對危機所採取的戰略對策: 適應、賠償和脫離。取自大流行期間有關的樣本本身已能就危機如何影響新生創業者的商務決策、提供獨特的啟示。