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The present study aims to examine the impact of social media marketing activities (SMMAs) on the adoption of food waste reduction behavior among Generation Z consumers within the restaurant service industry in Pakistan. The study focuses on the impact of social media advertisements and investigates the mediating influence of waste reduction intentions on actual behavior. This underscores the significance of contextual and emotional variables in comprehending consumer behaviors.

The study used a cross-sectional research methodology to examine the impact of SMMAs on the behavior of Generation Z consumers in Pakistan’s food service industry with regard to reducing food waste. A study was conducted to investigate the restaurant purchasing behaviors of a sample consisting of 449 individuals belonging to the millennial generation, often known as Generation Z.

The majority of variables related to SMMA, except for interactivity and personalization, were shown to have a positive impact on individuals’ intents to reduce food waste. The study observed a significant relationship between consumers’ intentions to decrease waste and their actual behavior in waste reduction. Furthermore, this relationship was shown to be influenced by the mediating role of waste reduction intention.

Examining how social media affects Pakistani Generation Z’s efforts to reduce food waste is what makes this study distinctive. According to the research, the majority of social media factors positively influence intentions to reduce waste. The relationship between intentions and actual behavior, which highlights the impact of social media campaigns and emotional aspects in promoting waste reduction, is one of the important conclusions.

This study aimed to examine the influence of psychological capital on the students' academic success in a PhD journey in Tanzania.

A cross-sectional survey design was used and data were collected through structured questionnaires from 200 PhD students in Tanzania. Confirmatory factor analysis was used to test the measurement model. The hypotheses were empirically tested using structural equation modeling (SEM).

The findings affirm that psychological capital in terms of hope, self-efficacy, resilience and optimism are significant predictors of students' academic success in a PhD journey.

To the best of the authors' knowledge, this paper is among the first to comprehensively examine the influence of psychological capital on students' academic success in PhD studies. Previous studies have primarily focused on the undergraduate level. Additionally, this study extends the applicability of conservation of resource (COR) theory to the context of PhD students, demonstrating that psychological capital serves as a crucial resource for them to achieve success in their PhD studies.

Existing Neighborhood Sustainability Assessment (NSA) tools such as “Leadership for Energy and Environmental Design - Neighborhood Development” (LEED-ND) and “Building Research Establishment Environmental Assessment Method” (BREEAM Communities) are widely criticized for a lack of transparency in the selection of indicators and an unbalanced focus on specific sustainability dimensions.

This paper asks how the expectations and use values of the professionals and residents involved in developing, designing, managing and living in a sustainable neighborhood can shape sustainability indicators that affect progress towards project goals. Taking as its focus The Sustainable City (TSC), a neighborhood in Dubai, United Arab Emirates (UAE), the paper develops data from in-depth, go-along interviews with 46 different actors.

Findings indicate that when given the opportunity to express their opinion, many actors will prioritize metrics different than the metrics dictated to the by sustainability experts and international rating systems. The findings suggest that NSA tools should place greater emphasis on local factors, public engagement and operational concerns.

The paper provides a method that any community can replicate to better understand the different use values of local actors and establish its own NSA tool. This can help experts learn how design, management and operational decisions interact to impact different dimensions of performance.

This paper recognizes sustainable neighborhoods as spaces with multiple identities. Hence, the indicators used to evaluate these neighborhoods need to be based on the expectations and use values of different actors. This paper proposes using the priorities of different local actors to reshape how these neighborhoods are assessed.

This paper aims to investigate the theoretical and practical links between digital twin (DT) application in heritage facilities management (HFM) from a life cycle management perspective and to signpost the future development directions of DT in HFM.

This state-of-the-art review was conducted using a systematic literature review method. Inclusive and exclusive criteria were identified and used to retrieve relevant literature from renowned literature databases. Shortlisted publications were analysed using the VOSviewer software and then critically reviewed to reveal the status quo of research in the subject area.

The review results show that DT has been mainly adopted to support decision-making on conservation approach and method selection, performance monitoring and prediction, maintenance strategies design and development, and energy evaluation and management. Although many researchers attempted to develop DT models for part of a heritage building at component or system level and test the models using real-life cases, their works were constrained by availability of empirical data. Furthermore, data capture approaches, data acquisition methods and modelling with multi-source data are found to be the existing challenges of DT application in HFM.

In a broader sense, this study contributes to the field of engineering, construction and architectural management by providing an overview of how DT has been applied to support management activities throughout the building life cycle. For the HFM practice, a DT-cum-heritage building information modelling (HBIM) framework was developed to illustrate how DT can be integrated with HBIM to facilitate future DT application in HFM. The overall implication of this study is that it reveals the potential of heritage DT in facilitating HFM in the urban development context.

Obtaining building permit certificate is an essential component of construction endeavors, but it can be cumbersome sometimes. The process is frequently beset with obstacles, including bureaucratic impediments, red-tapism, prolonged authorization protocols and insufficient inter-agency collaboration which result in project timeline extension, cost escalation and applicant dissatisfaction. Therefore, this study aims to examine customer satisfaction with the assessment of building construction permit certificates in Lalitpur, Nepal.

Following the notion of evaluation model theory, this study adopts an explanatory research design to determine the causal relationship between latent and observed variables. People who have recently completed the construction of their building and those people whose construction work is pending make up the population for the study. A total of 198 samples were collected by following the convenience sampling method from Lalitpur, Nepal. The primary data are collected by using the structured questionnaire with the interview process where the data are statistically evaluated using descriptive and inferential analysis using the KOBO toolbox, SPSS and AMOS. The connection between variables was examined using structural equation modeling (SEM).

Results indicate that the negligence of the employees, the attitude of the employees, the need for additional costs and the hiring of the agent are the most significant obstacles encountered by customers during the process of getting construction permit. Regarding the whole assessment system, the general population expresses displeasure. SEM results indicate that environment and quality are significantly related to customer satisfaction.

This paper's novelty lies in its Nepal-specific inquiry into the relationship between building permit acquisition procedures and customer contentment. The study provides a distinctive viewpoint on this context by combining evaluation model theory and SEM. The localized approach emphasizes the importance of customized strategies to improve customer satisfaction, adding to the current literature on the subject. The study's use of SEM as a quantitative analysis tool enhances its methodological rigor. This interdisciplinary research offers valuable insights for academics, practitioners and policymakers in Nepal and contributes to the wider field of construction and customer satisfaction.

The construction industry contributes to economic development by providing physical equipment and infrastructures. However, it also generates some undesirable outputs such as waste and environmental pollution, especially in developing countries. Due to the importance of the green supply chain management (GSCM) philosophy, for solving these problems, the current study aims to evaluate the drivers of GSCM adoption in the construction industry of Iran.

This research uses a descriptive and practical methodology. The participated experts in the study include senior managers of the construction department in Rasht municipality who had relevant academic education and suitable experiences in urban and industrial construction. The experts took part in both qualitative and quantitative phases of the research, namely verification of the drivers extracted from literature and ranking them in ascending order. In the quantitative phase, Step-Wise Weight Assessment Ratio Analysis (SWARA) as a new multi-criterion decision-making (MCDM) method is used to evaluate the drivers of GSCM adoption using MATLAB software.

The results show that environmental management systems, green product design and innovational capability with weights of 0.347, 0.218 and 0.143 are the most significant sub-drivers, respectively. The less important factor is an investment in environmental technology.

This study evaluated the motivational factors of GSCM in the construction industry. The findings help governments, companies and green supply chain (GSC) managers to improve their knowledge about GSCM and make the best decisions to decrease environmental pollution.

The purpose of this study is to investigate the impact of e-service quality and e-trust on customer e-satisfaction and, subsequently, on customer e-loyalty towards a website in the online shopping environment of Pakistan.

The research employed a quantitative approach and utilised structural equation modelling to investigate the relationship between e-service quality and e-trust on consumers’ e-satisfaction and e-loyalty. The data were collected from 250 individuals who actively use online shopping websites to purchase products in Pakistan.

The findings revealed that e-service quality and e-trust offered on e-commerce websites significantly impacted customer e-loyalty. However, it was found that both e-service quality and e-trust do not have a significant impact on customer e-satisfaction. In addition, the findings showed that customer e-satisfaction positively impacts e-loyalty.

Overall, these findings emphasise the importance of e-service quality, e-trust and customer e-satisfaction and their role in cultivating customer loyalty within the context of the online shopping environment in Pakistan.

This study contributes to the existing literature on online shopping in Pakistan by exploring the factors influencing consumer behaviour in this context. The findings add to the academic understanding of consumer behaviour and provide valuable insights for e-commerce businesses in Pakistan.

Studies concentrating on digitalization and interconnected capabilities have increased over the past several decades. Digitalization capability and open innovation are perceived as sources of sustained competitiveness across disciplines. This study investigated how digitalization capability and coopetition strategy affect the sustainable performance of firms by exploring the role of internal and external factors in influencing the adoption and success of open innovation in emerging markets.

To test the hypothesis, the authors conducted a structural equation model analysis on 509 firm datasets from the hub cities in China, an innovative battlefield where multilateral cooperation and competition are interwoven for globalization, clean development and the enhancement of economic growth.

The authors found that a firm's digitalization capability positively impacts outbound/inbound open innovation, coopetition strategy and sustainable performance. This study’s results support a series of mediating effects through outbound/inbound open innovation and coopetition strategy. Also, it provides a nuanced understanding of how digitalization capability and open innovation can affect sustainable performance in emerging markets.

The present study provides a nuanced understanding of how digitalization capability and in/out-bound open innovation can affect sustainable performance in emerging markets. The authors believe this model contributes to current knowledge by filling several research gaps, and this study’s findings offer valuable and practical implications for achieving open innovation and creating sustainable performance.

Effective green supply chain management (GSCM) has become a potentially valuable tool of securing competitive advantage and improving operational performance (OP) as competition is no longer exists between the firms but within green supply chains. The aim of this empirical study is to determine the link between GSCM practices (GSCMPs) and OP within the manufacturing sector of Bangladesh mediated by perceived competitive advantage (PCA). GSCMPs were divided into three further dimensions: green eco-design (GED), green supply chain partnering (GSCP) and internal green orientation (IGO).

The study selected 376 individuals as respondents who work as the top-level managers and the members of the Board of Directors at different Bangladeshi manufacturing firms through purposive sampling. A partial least square-based structural equation modeling (PLS-SEM) was utilized to identify the relationships between the three dimensions of, GSCMPs, and the single dependent variable, OP.

The study identified that two factors, GED and GSCP, have significant positive relationships with OP. On the other hand, another factor, IGO has a statistically insignificant relationship with OP. Regarding the mediating effects, the study identified that PCA can fully mediate the insignificant relationship between IGO and OP, and partially mediate the significant relationship between GSCP and OP. On the contrary, PCA has no mediating effect on the relationship between GED and OP.

This empirical study is an effort that examined the role of GSCMPs on the OP in the Bangladeshi manufacturing context. It is believed that this empirical investigation will prompt future theoretical studies and empirical experiments to enrich academia. Further, the findings of this study can serve as foundational guidance for policymakers and/or managers studying the formulation and implementation of GSCMP-related policies and strategies.

Managing mega infrastructure projects (MIPs) is more complex because of time, size, social, environmental and financial implications. This study aims to address the management approaches, complexity and risk factors involved in MIPs. The study focuses on project success criteria and their individual effects on the success of MIPs.

To address the challenges and identify the most influencing factor for the success of MIPs, the study deployed a cross-sectional survey approach. Six hundred eighty-two usable samples were collected from the respondents to understand the impact of predetermined factors on the success of MIPs. The structural equation model and artificial neural network approach were used to derive the importance of factors affecting the success of MIPs.

The study's outcome confirms that all three influencing factors: feasibility studies, community engagements and contract selection, have a significant positive impact on the success of MIPs. Community engagement amongst all three has the most influential predictor for the success of MIPs.

The developed model will enable practitioners and policymakers from Indian construction companies and other emerging nations to concentrate on recognized risk reduction variables to enhance project success criteria and project management success, especially for MIPs.