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This study aims to explore how project-based firms, which generally organize most of their work around temporary projects in discontinuous and fragmented types of business contexts, proactively formulate and implement digital transformation strategies under institutional pressures in a predigital era.

An exploratory case study was conducted in a large-scale construction company in China using multiple data collection methods, including semistructured interviews, documentation collection and observation.

An integrated framework is developed to conceptualize three key dimensions of digital transformation strategies of project-based firms: strategic adaptation for organization-environment fit through balancing the internal efficiency needs with the external legitimacy pressures; proactive business transformation through comprehensively managing the roles of digital technologies in optimizing defined business processes and fostering new business models; and delicate organizational transformation to integrate temporary project-level operation processes with ongoing firm-level business processes.

This study represents an exploratory effort to empirically investigate how project-based firms strategically organize complex digital transformation imperatives in their discontinuous and fragmented business contexts. The findings contribute to deepened understandings of how complex organizational and environmental contexts can be comprehensively managed for systemic business and organizational transformations to leverage the value of emerging digital technologies for project-based organizations.

The purpose of this article is based on the unit patent license fee model in the closed-loop supply chain.

This paper analyzes the impact of the bundling strategy of the retailer selling new products and remanufactured products on the closed-loop supply chain under the condition that the original manufacturer produces new products and the remanufacturer produces remanufacturing products.

The results show that alternative products can be bundled, and in many cases, the bundling of remanufactured products and new products is better than selling alone.

If the retailer chooses bundling, for the remanufacturer, when certain conditions are met, the benefits of bundling are greater than the separate sales at that time; for the original manufacturer, when the recycling price sensitivity coefficient is high, the bundling is better than separate sales.

This paper examines empirically how growth opportunities determine the relationship between corporate diversification and firm's value in an emerging economy.

This study employs annual data of Indonesian manufacturing firm's spanning five years. To test the potential nonlinear relationship between diversification and value, nonlinear regression model is employed. Baron and Kenny’s (1986) procedure is also employed to test the mediation role of the growth opportunities in the relation between diversification strategy and firm's value. This study also performs further robustness analysis on mediating role of growth opportunities on the relationship between diversification strategy and corporate value using path analysis approach.

The analyses reveal the U-shaped diversification and value relationship; this result suggests that the effect of diversification on value will vary across firms, the negative effect of diversification strategy on firm's value may reverse at higher levels of diversification. Further analysis indicates that such relationship is fully mediated by firm's growth opportunities.

Given the results, firms that are considering implementing diversification strategy should seek the optimal level of diversification to gain diversification premium. Furthermore, the manager should observe the best opportunities available for the firm before undertaking the diversification strategies.

This paper contributes to the existing literature on diversification strategy by extending the insight of this research area of a large emerging economy, on which prior studies have not reached conclusive results.

Adopting adaptive behavior has become a basic measure for farmers because the increasingly severe climate change is affecting agricultural production. Perception is a critical first step in adopting adaptive behaviors. Livelihood resilience represents a farmer's ability to adapt to climate change. Therefore, this article aims to explore the impact of livelihood resilience and climate change perception on the climate change adaptation behavior of farmers in the Qinling Mountains region of China.

In this study, 443 micro-survey data of farmers are obtained through one-on-one interviews with farmers. The Logit model and Poisson regression model are used to empirically examine the impact of farmers' livelihood resilience and climate change perception on their climate change adaptation behaviors.

It was found that 86.68% of farmers adopt adaptive behaviors to reduce the risks of facing climate change. Farmers' perception of extreme weather has a significant positive impact on their adaptive behavior under climate change. The resilience of farmers' livelihoods and their perception of rainfall have a significant positive impact on the intensity of their adaptive behavior under climate change. Climate change adaptation behaviors are also different for farmers with different levels of livelihood resilience.

Based on the results, policy recommendations are proposed to improve farmers' perception of climate change, enhance the sustainability of farmers' adaptive behavior to climate change, strengthen emergency management and infrastructure construction and adjust and upgrade farmers' livelihood models.

Coastal zone ecological restoration project is of great significance to alleviate marine ecological degradation. Evaluating the effect of coastal ecological restoration projects and identifying the obstacle factors affecting their restoration level can provide an empirical basis for future Marine ecological restoration projects.

However, due to the initial stage of coastal zone ecological restoration projects, the actual monitoring data of coastal zone ecological restoration is relatively lacking. Based on the CRITIC-TOPSIS (combination of CRITIC method and TOPSIS method) method, combined with the subjective perception of the public and the actual data of the restoration project, this paper proposes an evaluation method of the coastal zone ecological restoration effect to obtain the specific implementation effect of the coastal zone ecological restoration project. The main obstacle factors affecting the evaluation of coastal ecological restoration effect are identified by using the obstacle degree model.

This paper conducted an empirical study on the restoration of sandy shoreline and coastal wetland in Qinhuangdao city. Based on the data of restoration projects and the subjective perception of ecological restoration by the public in Qinhuangdao city, the research results showed that the coastal zone ecological restoration effect of Qinhuangdao city was general. The quality of the restoration project and the public perception have an important influence on the evaluation of the restoration effect. Improving the quality of the restoration project, strengthening the public's participation in ecological restoration and allowing the public to better participate in the ecological restoration of the coastal zone can improve the effect of ecological restoration of the coastal zone in an all-round way.

The research results of this paper have a guiding role in the ecological restoration of coastal cities in the future, and also have a demonstration and reference role for the assessment of the effect of ecological restoration of coastal zones.

The purpose of this paper is to increase the understanding of how warehouse operations and design are affected by the move toward integrated omni-channels.

A structured literature review is conducted to identify and categorize themes in multi- and omni-channel logistics, and to discuss how aspects related to these themes impact and pose contingencies for warehouse operations and design.

The review revealed a lack of focus on warehouse operations and design in multi- and omni-channels. Instead, most articles published in scientific journals discuss changes in consumer demand and implications for the network level, concerning aspects such as the organization and management of material and information flows, inventory management, resources, actors and relationships. Ten themes in omni-channel logistics were identified and grouped into two categories: the value proposition and channel management; and the physical distribution network design. The themes and related aspects have implications for warehousing, and by combining these with general warehousing knowledge, the authors derive a comprehensive and structured agenda is derived to guide future research on omni-channel warehousing.

This paper outlines a research agenda, including detailed research questions, for advancing the theory on warehouse operations and design in omni-channels.

The agenda can inspire practitioners in their work to understand the upcoming challenges and address relevant issues in omni-channel warehousing, taking into consideration its interdependence with value proposition, channel management and network decisions.

This is the first comprehensive review focusing on and synthesizing available literature on omni-channel warehousing. This topic has until now received limited coverage but is of increasing importance to scholars in the field.

This study aims to develop a model based on the financial variables for better accuracy of financial distress prediction on the sample of private French, Spanish and Italian firms. Thus, firms in financial difficulties could timely request for troubled debt restructuring (TDR) to continue business.

This study used a sample of 312 distressed and 312 non-distressed firms. It includes 60 French, 21 Spanish and 231 Italian firms in both distressed and non-distressed groups. The data are extracted from the ORBIS database. First, the authors develop a new model by replacing a ratio in the original Z”-Score model specifically for financial distress prediction and estimate its coefficients based on linear discriminant analysis (LDA). Second, using the modified Z”-Score model, the authors develop a firm TDR probability index for distressed and non-distressed firms based on the logistic regression model.

The new model (modified Z”-Score), specifically for financial distress prediction, represents higher prediction accuracy. Moreover, the firm TDR probability index accurately depicts the probabilities trend for both groups of distressed and non-distressed firms.

The findings of this study are conclusive. However, the sample size is small. Therefore, further studies could extend the application of the prediction model developed in this study to all the EU countries.

This study has important practical implications. This study responds to the EU directive call by developing the financial distress prediction model to allow debtors to do timely debt restructuring and thus continue their businesses. Therefore, this study could be useful for practitioners and firm stakeholders, such as banks and other creditors, and investors.

This study significantly contributes to the literature in several ways. First, this study develops a model for predicting financial distress based on the argument that corporate bankruptcy and financial distress are distinct events. However, the original Z”-Score model is intended for failure prediction. Moreover, the recent literature suggests modifying and extending the prediction models. Second, the new model is tested using a sample of firms from three countries that share similarities in their TDR laws.

Human resources can differentiate firms from their competitors or directly affect the success or failure of firms. As in many sectors, there is a need for qualified employees in the logistics sector, which is of great importance for the national economies. Qualified employees in this sector contribute to the success of the companies and the development of the industry. In this study, it is aimed to reveal the qualifications and characteristics of the labour force needed by logistics companies. It was also aimed to show the impact of COVID-19 on logistics job ads. For this purpose, a total of 1,410 job vacancy postings (before COVID-19) and a total of 1,700 job vacancy postings (during COVID-19) were searched on the kariyer.net website with the word “logistics” and analysed by content analysis method. As a result, it was found that the most advertised province was Istanbul in both periods, the most looked up experience requirement in the candidates was 1-5 years in both periods, the opportunities provided to the candidates (transportation, food and beverage, career, social activity) were not mentioned much in both periods. This study reveals the status of logistics job postings in the period before COVID-19 and during COVID-19. It was also aimed to show the impact of COVID-19 on logistics job ads. We investigated whether the logistics employee demand has changed and whether the pandemic is affecting workforce characteristics. This is the first empirical analysis of the impact of COVID-19 on logistics vacancy postings.

Logistical facility location decisions can make a crucial difference in the success or failure of a company. Geographical Information Systems (GIS) have recently become a very popular decision support system to help deal with facility location problems. However, until recently, GIS methodologies have not been fully embraced as a way to deal with new facility location problems in business logistics. This research makes a framework for categorizing empirical facility location problems based on the intensity of the involvement of GIS methodologies in decision making. This framework was built by analyzing facility location models and GIS methodologies. The research results revealed the depth of the embracement of GIS methodologies in logistics for determining new facility location decisions. In the new facility location decisions, spatial data inputs are almost always coupled with the visualization of the problems and solutions. However, the usage of GIS capability solely (i.e. suitability analysis) for problem solving has not been embraced at the same level. In most cases, the suitability analysis is used together with special optimization models for choosing among the multiple alternatives.