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This study elicits the critical attributes, consequences and values associated with the purchasing process in the context of cross-border e-commerce (CBEC). The purpose is to provide a better understanding of the fundamental factors that determine consumer values in CBEC.

The study applies the means-end-chain theory and soft-laddering techniques to interview 60 CBEC consumers to construct an implication matrix and a hierarchical value map (HVM) of the consumer purchasing process, consisting of attribute-consequence-value (A-C-V) paths.

By analyzing the significant linkages, elements, ladders and chains in the HVM, four dominant A-C-V paths were identified: economic-driven, efficiency-driven, progress-driven and quality-driven paths.

This study included only Chinese CBEC buyers. This limitation might affect the generalizability of the conclusions as culture, purchase habits and economic development differ between China and other countries.

The results of this study provide CBEC practitioners an understanding of the consumer purchasing process and how consumer values are associated with platform characteristics. Thus, the results aid practitioners in allocating resources and developing CBEC platforms in an appropriate manner and direction.

This study sheds lights on the emerging phenomenon of CBEC. By applying the means-end-chain approach, the study provides a comprehensive HVM for interpreting the consumer online purchasing process in this novel context. By illustrating the dominant paths, this research provides deeper theoretical insights into the specific focuses of CBEC consumer purchasing.

Prior research does not provide a clear picture of how managers can effectively manage customer in-role and extra-role behaviours in a retail setting. This study aims to test the differential impact of the two main customer relationship predictor paths – identity-based and satisfaction-based paths – on customer in-role and extra-role behaviours.

A random sample of 500 customers from the flagship store of an up-market, international department store chain participated in a written survey. Purchase spending data for each customer was obtained from the retailer’s loyalty card database.

The two studied predictor paths possess a differential impact on customer extra-role behaviours. Civic virtue and co-creation behaviours are exclusively driven by the identity-based path, whereas sportsmanship is driven solely by the satisfaction-based path. Moreover, the identity-based path impacts purchase behaviour only when symbolic purchase motivation is high. Overall satisfaction has no impact on purchase behaviour.

In some retailing contexts, extra-role behaviours such as co-creation or civic virtue might simply be irrelevant (e.g. discount chains).

Managers, who have the intention to stimulate customers to give constructive feedback on products or services, or to involve them in co-creation activities, are well advised to also invest in identity-based path activities.

This study is the first to empirically test the effects of customer identification and overall customer satisfaction on the various dimensions of customer in-role and extra-role behaviours. Customer extra-role behaviours should not be conceptualised as one global construct but should comprise distinct dimensions of discretionary behaviours that have different antecedents.

Functioning as space connectors, path structures in urban parks may rarely present social interaction opportunities, although centralized activity spaces are available. This paper investigated the interrelationships between the visual and physical accessibility attributes of path structure and their impacts on passive social interaction intensity across urban parks in Kuala Lumpur.

The concept of social interaction has been studied elsewhere in social cohesion, social affiliation and sense of communication. Still, it has not been studied in the context of urban park design. This study employed mixed methods using an adaptive and unique combination of qualitative and quantitative data collections to analyze urban parks with a bit of visual vegetation barrier. The experiential landscape method was applied to determine visual accessibility by interpreting experiential landscape maps. The space syntax method based on quantitative analysis is considered to measure physical accessibilities and vigorous activities along the designated paths by conducting integration analysis and gate observation. The data were crossed-analyzed using a Geographic Information System (GIS) classification technique, correlation analysis and Microsoft combo-charts to generate the relationship between patterns of activities and their accessibilities.

The results suggested that designated paths with higher accessibility attributes, impressively more elevated than other tracks, could influence the intensity of passive social interactions. The findings supported the understanding that activity nodes and active areas adjoining designated routes could make accessibility attribute areas more critical. These findings verify that visually enriching the spaces along the path structure toward activities is a pivotal contributor to urban planners and designers to enhance the paths’ local integration (LI) and visual accessibility to predict more passive eye contact among park visitors.

The proposed interrelationship among variables in this study has limitations because of not considering other qualitative methods and techniques like cognitive maps and interview simultaneously. These techniques could discover why some paths generate more passive eye contact among park users (Mohammadi Tahroodi, 2018).

Kuala Lumpur Structure Plan 2020 emphasizes Kuala Lumpur’s unique image as a tropical garden city via preserving and developing the iconic historical urban parks in the city center (CHKL, 2004, pp. 3–3). The latest Draft Kuala Lumpur Structure Plan 2040 has outlined the strategy to achieve a conducive, good-quality neighborhood that encourages social interaction. The findings could assist urban planners and designers better public parks by considering accessibility and permeability aspects of design. This research endorses the appropriateness of interrelationship between accessibility attributes of path structure and social interaction in urban design research, which local urban designers have not fully considered until now. Evaluating the visual convenience of designated paths and assessing LI of the axial lines constructing each designated route of urban parks during the primary stage could enable urban designers to estimate to what extent the paths are accessible and respond to passive social interaction. Then they could enrich with salient landmarks, views and activity nodes to make them attractive. The considerable number of designated paths connections, specifically while they shape the sides of activity nodes, could increase the connectivity and integration of spaces within the parks. These patterns of positioning the activity nodes make the designated routes more legible and provide ease of movement. As a result, it will give urban park users more information about the activities. Allowing people to use the paths will increase people’s presence and, subsequently, passive social interaction. One way is to locate accessible lands that provide social activities at direct visual access paths within urban parks for legibility.

The socially responsive urban design enhances the quality of life and provides life satisfaction, happiness and society’s overall health. Being in urban social parks in any passive and active situations has psychological benefits. It facilitates relief and rests from a stressful modern lifestyle that significantly impacts their mental health and well-being. The framework applied in this research integrates the social, spatial and physical aspects of parks design. With this regard, principles and indicators facilitate physically and socially attractive urban parks for Kuala Lumpur city center and applicable to similar contexts elsewhere.

The concept of social interaction has been studied elsewhere in social cohesion, social affiliation and sense of communication. Still, it has not been studied in the context of urban park design. This study employed mixed methods using an adaptive and unique combination of qualitative and quantitative data collections to analyze urban parks with a bit of visual vegetation barrier.

In the face of major disasters, the Chinese people's willingness to donate has increased and the result is that the donation paths have increased. However, there are certain differences in the choice of donation paths for different types of individuals. It is crucial to pay more attention to the attitude and donation path selection of donors and propose strategies to promote individual donation behavior. The purpose of this study is to propose a conceptualized moderated mediation model for testing the linkage between individual attitude and donation path selection through the mediating effect of donors' behavioral intention and the moderating effect of behavioral difficulty perception or social pressure between donors' attitude and their donation path selection.

Based on a questionnaire survey of 628 community workers during COVID-19 in China. Self-reported measures were used to obtain data on IA, BI, SP, BDP and DPS. Survey data were used to test the proposed model using hierarchical regression analysis. Mediation analyses with bootstrap via PROCESS were used to ascertain the proposed relationship.

The results showed that individual attitude are positively related to donation path selection. Moreover, this study finds that behavioral intention serves as a mediator in the relationships between individual attitude and donation path selection. The social pressure and behavioral difficulty perception negatively moderate the relationship between individual attitude and behavioral intention.

There are still some shortcomings in this study: First, although the data collected at multiple points in this study are all individual data. Future research can add evaluations of relatives, friends or colleagues to individual scheduling of survey subjects to reduce homology errors. Second, although this study has verified the mediating role of the opposite sex, some of the mediating results show that there may be other variables that play a role in the relationship between individual attitudes and donation path selection. In the research on path selection, the integrated theoretical perspective has rich connotations but has not attracted enough attention from the academic community. This research is only based on this single theoretical perspective to construct, verify and explain the model, and there should be other integrated theories. The fit point can be used to analyze the influence mechanism of individual attitudes on the choice of donation path.

First of all, we must deepen our understanding of the connotation and role of individuals' attitudes. In the event of a major epidemic, the following two types of measures will be taken to improve individuals' attitudes toward specific donation paths: First, the sponsors of each donation should do their best to donors and provide more information about donations, because the more information resources they have, the stronger the experience of the corresponding donation path, and the more they will choose the path. The sponsor of the second donation must show concern for major epidemics that are prone to occur and a desire to help people affected by disasters, so as to enhance the emotional identity of the donor, thereby increasing the probability of the donor choosing a specific donation path. Secondly, donation sponsors should be wary of the negative influence of social pressure on the donation path selection of individual donors. Donation sponsors can train individuals who are willing to donate, guide them in social relations, online public opinion and other pressure methods and improve the possibility of individuals choosing specific donation routes.

Deepen the understanding of the content and effectiveness of the behavioral difficulty perception that has a profound impact on the donor. The greater the tendency to make a path choice is often affected by the individual's perception of the difficulty of behavior. The perception of difficulty of a certain donation path will cause the individual to retreat and inhibit the possibility of the individual choosing the path. Therefore, donation sponsors should take all measures to make their own donation channels simpler and more efficient, thereby reducing the individual's perception of the difficulty of donation behavior.

Drawing on TPB theory, a theoretical framework is constructed that specifies the process through which individual attitude affects donation path selection to expand collective understandings of individual attitude in the donation context. Furthermore, the boundary conditions of the underlying process are investigated, which further enhances the contribution of this paper to the extant literature on individual attitude.

This study investigates how artificial intelligence (AI) chatbots persuade customers to accept their recommendations in the online shopping context.

Drawing on the elaboration likelihood model, this study establishes a research model to reveal the antecedents and internal mechanisms of customers' adoption of AI chatbot recommendations. The authors tested the model with survey data from 530 AI chatbot users.

The results show that in the AI chatbot recommendation adoption process, central and peripheral cues significantly affected a customer's intention to adopt an AI chatbot's recommendation, and a customer's cognitive and emotional trust in the AI chatbot mediated the relationships. Moreover, a customer's mind perception of the AI chatbot, including perceived agency and perceived experience, moderated the central and peripheral paths, respectively.

This study has theoretical and practical implications for AI chatbot designers and provides management insights for practitioners to enhance a customer's intention to adopt an AI chatbot's recommendation.

1. The study investigates customers' adoption of AI chatbots' recommendation.

2. The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

3. The central and peripheral cues are generalized according to cooperative principle theory.

4. Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

5. Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

6. Customers' mind perception positively moderates the central and peripheral paths.

The study investigates customers' adoption of AI chatbots' recommendation.

The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

The central and peripheral cues are generalized according to cooperative principle theory.

Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

Customers' mind perception positively moderates the central and peripheral paths.

Employees are increasingly expected to organize their own human resource development activities. To what extent and how exactly employees in various organizational contexts manage to shape their individual learning paths however remains largely unclear. The purpose of this present study is to explore, leaning on the empirical Learning-Network Theory (LNT) research and its findings, how employees in different occupations create learning paths that are attuned to their specific work context.

The paper reviews 23 MSc theses based on 14 distinct data sets collected between 2005 and 2015, containing approximately 1,484 employees from some 45 organizations and across various professions. The teachers, nurses, postal, software, telecom, railway and logistics company employees were mostly based in the Netherlands. The analysis focuses on learning-path types and learning-path strategies found in the 23 studies.

Motives, themes, activities, social contexts and facilities were found to be instrumental in explaining differences among individual learning paths. A total of 34 original learning-path types and strategies were found to cluster under 12 higher-order labels. Some of these were based on learning motive, some on learning theme, some on core learning activities, some on social learning context and a few on a combination of these elements. Overall, the socially oriented learning-path strategy was the most prevalent, as it was found among nurses, employees of software/postal/telecom, railway and logistics company employees, as well as teachers in two schools.

The paper presents the first overview of empirical studies on employee learning path(s) (strategies). In addition, it strengthens the empirical basis of the LNT.

Crowdfunding (CF) has become an increasingly popular means of financing for entrepreneurs and has attracted significant attention from both researchers and practitioners in recent years. The purpose of this study is to investigate the core content and knowledge diffusion paths in the CF field. Specifically, we aim to identify the main topics and themes that have emerged in this field and to trace the evolution of CF knowledge over time.

This study employs co-word clustering and main path analysis (MPA) to examine the historical development of CF research based on 1,528 journal articles retrieved from the Web of Science Core Collection database.

The results of the analysis reveal that CF research focuses on seven themes: sustainability, entrepreneurial finance, entrepreneurship, fintech, social entrepreneurship, social capital, and microcredits. The analysis of the four main paths reveals that equity CF has been the dominant topic in the past years. Recently, CF research has tended to focus on topics such as fintech, the COVID-19 pandemic, competition, Brexit, and policy response.

To the authors' best knowledge, this is the first attempt to explore knowledge diffusion dynamics in the CF field. Overall, the study offers a structure for analyzing the paths through which knowledge is diffused, enabling scholars to effectively manage a large volume of research papers and gain a deeper understanding of the historical, current, and future trends in the development of CF.

Prefabricated building has been widely applied in the construction industry all over the world, which can significantly reduce labor consumption and improve construction efficiency compared with conventional approaches. During the construction of prefabricated buildings, the overall efficiency largely depends on the lifting sequence and path of each prefabricated component. To improve the efficiency and safety of the lifting process, this study proposes a framework for automatically optimizing the lifting path of prefabricated building components using building information modeling (BIM), improved 3D-A* and a physic-informed genetic algorithm (GA).

Firstly, the industry foundation class (IFC) schema for prefabricated buildings is established to enrich the semantic information of BIM. After extracting corresponding component attributes from BIM, the models of typical prefabricated components and their slings are simplified. Further, the slings and elements’ rotations are considered to build a safety bounding box. Secondly, an efficient 3D-A* is proposed for element path planning by integrating both safety factors and variable step size. Finally, an efficient GA is designed to obtain the optimal lifting sequence that satisfies physical constraints.

The proposed optimization framework is validated in a physics engine with a pilot project, which enables better understanding. The results show that the framework can intuitively and automatically generate the optimal lifting path for each type of prefabricated building component. Compared with traditional algorithms, the improved path planning algorithm significantly reduces the number of nodes computed by 91.48%, resulting in a notable decrease in search time by 75.68%.

In this study, a prefabricated component path planning framework based on the improved A* algorithm and GA is proposed for the first time. In addition, this study proposes a safety-bounding box that considers the effects of torsion and slinging of components during lifting. The semantic information of IFC for component lifting is enriched by taking into account lifting data such as binding positions, lifting methods, lifting angles and lifting offsets.

Artificial intelligence (AI)-based systems can save the lives of many people by assessing the safety of flight paths. Unfortunately, the world witnessed a horrible event in January 2020 with the case of flight 752 of Ukrainian International Airlines from Tehran to Kiev and it has prompted us to ask how AI can prevent such events by warning to flight path planners. This paper aims to propose a framework for assessing the safety of flight paths from a shooting of an airplane by air defense systems installed on the path. Unlike the existing studies, this study takes a new look at pre-flight risk assessment by using textual information in social and news networks. To this end, the authors use existing information retrieval techniques to identify high flight risk areas by examining the news articles, comments, posts, tweets, etc., in social media and then estimate the probability of targeting a passenger aircraft by the air defense systems probably installed on high-risk areas with the help of a statistical model. This estimation can then be used by fight planners to avoid such events.

To design a framework for estimating the probability of a fatal shooting of an airplane by air defense systems installed on its flight path, the authors have used the idea of information retrieval in conjunction with statistical methods. The authors have extracted some significant variables in the shooting of flights and proposed an AI-based framework to estimate the probability of a fatal shooting of an airplane during its flight and sketched a case study for using machine learning approaches to assist with flight path planning. As a case study, the authors covered flight 752 to explain the usefulness of the proposed framework in this context.

Unlike the existing methods, this study investigates flight path safety assessment from the social media and crowdsourcing perspective. In this study, the authors proposed an AI-based framework to avoid aviation hazards by estimating the probability of a shooting of an airplane by air defense systems installed on its flight path. Moreover, this study was designed to show how estimating the safety of flight paths by using AI-based methods can help flight planners to avoid such events and gain further insights into the use of AI-based systems in pre-flight risk assessment.

The idea behind the proposed method is original and as the authors’ best knowledge, there is no similar framework using social media for flight path safety assessment.

International technology transfer (TT) initiatives are essential for developing the necessary infrastructure which underpins the sustainable development of economics and living standards in newly industrialised and developing countries. However, these initiatives have rarely translated into enhanced capabilities and competitiveness within host country firms, resulting in a sustained reliance on foreign firms. With few clues as to how to effectively manage the TT process, many stakeholders from the construction sectors of developing countries lack direction on how to more rapidly diffuse best‐practice technology. This paper aims to address the issues.

In an attempt to better understand, the international TT process on Thai construction projects a path model was developed and later implemented. The path model development stage utilised the questionnaire survey response of 162 Thai construction and engineering professionals that had exposure to construction projects which incorporated international TT initiatives. A rigorous statistical analysis process which employed ANOVA, exploratory factor analysis, confirmatory factor analysis and structural equation modelling was followed to formulate the robust path model. The path model implementation stage utilised a series of case studies to validate the significant path equations in the developed model. This stage solicited questionnaire survey responses from 47 Thai construction and engineering professionals working for five domestic firms which were contractually involved with foreign partners on four large construction projects.

The findings provide evidence that transferors must have appropriate characteristics (i.e. willingness, knowledge base, experience, management, etc.) for establishing solid relationships with the transferee. Moreover, relationship building (RB) between the transferor and transferee (i.e. trust, understanding, communication, etc.) is the key enabler to TT induced value creation for the host construction sector.

The developed model empirically explains interactions between TT process enablers and outcome factors in the construction context. The model can assist government and private sector organisations from developing and newly industrialised countries to better evaluate the TT induced value creation process for the host construction sector. In this context, improved TT evaluation can help such organisations to devise targeted strategies for accelerating rates of TT, which will ultimately decrease their reliance on foreign firms when procuring large‐scale infrastructure projects.