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Due to rapid digitalization, the emergence of the “phygital” environment, which blends physical and digital experiences, creates unique challenges for researchers. This paper aims to introduce an interpretivist methodological framework designed to understand consumer behavior in phygital environments. The framework enables an in-depth exploration of the contextual factors, subjective experiences, personal emotions and social networks that influence consumer behavior in this space.

The framework was developed after a thorough literature review of the phygital environment and interpretivist research landscape. Consistent with the phygital transformation theory, this approach allows researchers to go beyond the limitations of purely quantitative methods, gaining a deeper understanding of consumer behavior in phygital environments. The framework is organized into four meticulously designed pillars, each focusing on specific aspects of research and using distinct data collection and analysis approaches.

The systematic framework facilitates exploration of various dimensions of consumer experiences in phygital settings through qualitative research techniques. Uncovering the richness of contextual factors, subjective meanings, consumer experiences and social interactions within the phygital environment yields meaningful insights into consumer decision-making and preferences. These insights help marketers craft better phygital marketing strategies.

This interpretivist framework presents a unique approach for researchers hoping to investigate consumer behavior in phygital environments. It offers deep insights and understanding of this largely unexplored space, contributing to the evolving body of knowledge in phygital studies.

In the digital economy, what are the strategies of multinationals from developed countries and emerging markets? How do regulations in the home country affect their growth? Recent digital multinationals in diverse national and institutional contexts raise questions that require new approaches in international business (IB) studies. This chapter examines two leading firms in the global e-commerce industry: Amazon and Alibaba. We compare their digital capabilities and physical asset-building strategies over the past two decades and we connect the Internet governance environment in the United States and China with their business models and internationalization patterns. We argue that despite the platform and global nature of Amazon’s and Alibaba’s activities, the recent moves of governments across the world to regulate Internet governance poses an important challenge for digital multinationals. This research features a comparative analysis of two prominent digital multinationals and identifies a promising area for future IB strategy studies.

Recent reports based on the sustainable development goals (SDGs) have revealed that no country is in line with achieving the targets of the 2030 Agenda for sustainable development, with the slowest progress being witnessed mainly on goals that are focused on the environment. This study examines environmental performance indicators for assessing the sustainability of building projects.

The study uses an explanatory sequential design with an initial quantitative instrument phase, followed by a qualitative data collection phase. An extensive critical comparative review of the literature resulted in the identification of ten environmental sustainability indicators. One hundred and sixty-seven questionnaire responses based upon these indicators from the Ghanaian construction industry were received. Data were coded with SPSS v22, analysed descriptively, and via inferential analysis. These data were then validated through semi-structured interviews with six interviewees who are fellows of their respective professional bodies, a senior academic (professor in construction project delivery) and a government official. Data obtained from the semi-structured validation interviews were analysed through the side-by-side comparison of the qualitative data with the quantitative data.

The findings from the study suggest that all the indicators were important in assessing building projects' environmental sustainability across the entire life cycle. Key among the identified indicators is the effects of the project on “water quality, air quality, energy use and conservation, and environmental compliance and management”. The interviewees further agreed to and confirmed the importance of these identified indicators for assessing the environmental sustainability of building projects in Ghana.

Compared to existing studies, this study adopts the exploratory sequential design to identify and examine the critical indicators in assessing the environmental sustainability across the entire lifecycle of building projects in a typical developing country setting, i.e. Ghana. It reveals areas of prime concern in the drive to place the local construction industry on a trajectory towards achieving environmental sustainability.

This paper aims to investigate the process of innovation in firms founded by user-entrepreneurs. It also empirically investigates the role of customer involvement and user-entrepreneurs’ learning goal orientation in the innovation process.

A survey design is used to collect data from entrepreneurs managing small businesses. A total of 255 entrepreneurs responded to the survey questionnaire. The partial least square structural equation model was used to test the measurement and structural model.

Results suggest a positive association of user-entrepreneurship with innovation and customer involvement. Results also confirmed that customer involvement mediates the relationship between user-entrepreneurship and innovation. In addition, results suggest that the higher learning orientation (LO) of user-entrepreneurs plays a vital role in innovation by strengthening the relationship between user-entrepreneurship and customer involvement.

The study focuses on small entrepreneurial firms with less than equal to or less than 250 employees. The results may not be generalizable to larger user-entrepreneurial firms. Also, this study is based on American entrepreneurs. Therefore, the results may not be generalizable to other countries.

Evidence for the role of customer involvement and LO in the innovation process can be used by entrepreneurs and small business owners in hiring and training decisions. Also, the findings suggest the important role played by customers in the innovation process. Firms can use this insight to involve their customers in the product development process to secure better innovation outcomes.

This study contributes to the innovation and entrepreneurship literature by emphasizing the critical role of customer networks in user-entrepreneurs’ innovation performance. It offers a process model that offers empirical evidence supporting the positive role of customer involvement in new ventures. It highlights the role of the LO of user-entrepreneurs in the customer engagement process.

High-strength martensitic steels having strong hydrogen embrittlement (HE) susceptibility and the metal carbide (MC) nanoprecipitates of microalloying elements such as Nb, V, Ti and Mo in the steel matrix can effectively improve the HE resistance of steels. This paper aims to review the effect of MC nanoprecipitates on the HE resistance of high-strength martensitic steels.

In this paper, the effects of MC nanoprecipitates on the HE resistance of high-strength martensitic steels are systematically described in terms of the types of MC nanoprecipitates, the influencing factors, along with numerical simulations.

The MC nanoprecipitates, which are fine and semicoherent with the matrix, effectively improve the HE resistance of steel through the hydrogen trapping effects and microstructure optimization, but its effect on the HE resistance of steel is controlled by its size, number and distribution state.

This paper summarizes the effects and mechanisms of MC nanoprecipitates on HE performance of high-strength martensitic steel and provides the theoretical basis for corrosion engineers to design high-strength martensitic steels with excellent HE resistance and improve production processes.

CEO incentive contracts are commonplace in China but their incidence varies significantly across Chinese cities. We show that city and provincial policy experiments help explain this variance. We examine the role of two policy experiments: the use of Special Economic Zones (SEZs) to attract Foreign Direct Investment (FDI), and the privatisation of State-Owned Enterprises (SOEs). The introduction of SEZs is found to be uncorrelated with the prevalence of CEO incentive contracts. However, firms are more likely to use such contracts in areas that saw rapid SOE privatisation, irrespective of the firm’s own current ownership status and irrespective of the size of the SOE sector in the late 1970s. The positive effect of privatisation is robust to various estimation techniques and model specifications. These findings suggest that domestic privatisation policies have been more influential than FDI in driving the expansion of incentive contracts in China.

This chapter examines the potential and limitations of criminal law as a policy tool for fighting against the trade in counterfeit goods in Tanzania. It uncovers major challenges involved in tackling the counterfeiting business in Tanzania using criminal law. The chapter shows that counterfeit goods have infiltrated many supply chains in Tanzania. Both law-related and non-law factors drive the counterfeit goods trade. The counterfeiting business affects consumers, traders, the economy and the general society in Tanzania. The counterfeiting business presents serious societal risks during the crises such as the COVID-19 pandemic owing to the possible infiltration of counterfeit pharmaceuticals into the medical supply chain. Criminal law is part of Tanzania's legal embodies for fighting against the counterfeit goods trade. Both law-related and non-law limitations and challenges undermine the efficacy of criminal law in tackling the trade in counterfeit goods in Tanzania. The chapter recommends policy, legal and institutional reforms that will help to augment the efficacy of the anti-counterfeiting legal regime in Tanzania.

With the rapid growth of the domestic lending industry, assessing whether the borrower of each loan is at risk of default is a pressing issue for financial institutions. Although there are some models that can handle such problems well, there are still some shortcomings in some aspects. The purpose of this paper is to improve the accuracy of credit assessment models.

In this paper, three different stages are used to improve the classification performance of LSTM, so that financial institutions can more accurately identify borrowers at risk of default. The first approach is to use the K-Means-SMOTE algorithm to eliminate the imbalance within the class. In the second step, ResNet is used for feature extraction, and then two-layer LSTM is used for learning to strengthen the ability of neural networks to mine and utilize deep information. Finally, the model performance is improved by using the IDWPSO algorithm for optimization when debugging the neural network.

On two unbalanced datasets (category ratios of 700:1 and 3:1 respectively), the multi-stage improved model was compared with ten other models using accuracy, precision, specificity, recall, G-measure, F-measure and the nonparametric Wilcoxon test. It was demonstrated that the multi-stage improved model showed a more significant advantage in evaluating the imbalanced credit dataset.

In this paper, the parameters of the ResNet-LSTM hybrid neural network, which can fully mine and utilize the deep information, are tuned by an innovative intelligent optimization algorithm to strengthen the classification performance of the model.