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In 2020, the logistics market in Malaysia was valued at USD 37.60 billion, and it is projected to grow to more than USD 55.0 billion by 2026 at a compound annual growth rate (CAGR) of more than 4%. However, more information is needed about the impact of green logistic practice determinants by the local SMEs on the market share. This study serves as a focal point by examining the factors involved by offering a conceptual framework of determinants and their potential outcomes. This study contributes by demonstrating a conceptual, theoretical framework derived from the synthesis of two theory such as the Resource-Based View theory and the Diffusion of Innovation Theory. At the same time, it offers a holistic approach with an in-depth understanding of the Technological and Organizational factors of SMEs. The relationship between the implementation of green practices and organizational performance is also explored.

Docking technology plays a crucial role in enabling long-duration operations of autonomous underwater vehicles (AUVs). Visual positioning solutions alone are susceptible to abnormal drift values due to the challenging underwater optical imaging environment. When an AUV approaches the docking station, the absolute positioning method fails if the AUV captures an insufficient number of tracers. This study aims to to provide a more stable absolute position visual positioning method for underwater terminal visual docking.

This paper presents a six-degree-of-freedom positioning method for AUV terminal visual docking, which uses lights and triangle codes. The authors use an extended Kalman filter to fuse the visual calculation results with inertial measurement unit data. Moreover, this paper proposes a triangle code recognition and positioning algorithm.

The authors conducted a simulation experiment to compare the underwater positioning performance of triangle codes, AprilTag and Aruco. The results demonstrate that the implemented triangular code reduces the running time by over 70% compared to the other two codes, and also exhibits a longer recognition distance in turbid environments. Subsequent experiments were carried out in Qingjiang Lake, Hubei Province, China, which further confirmed the effectiveness of the proposed positioning algorithm.

This fusion approach effectively mitigates abnormal drift errors stemming from visual positioning and cumulative errors resulting from inertial navigation. The authors also propose a triangle code recognition and positioning algorithm as a supplementary approach to overcome the limitations of tracer light positioning beacons.

In the stock market, herding behavior occurs when investors mimic the actions of others in their investment decisions. As a result, the market becomes inefficient and speculative bubbles form. This study aims to investigate the relationship between information, overconfidence, market sentiment, experience and national culture, and herding behavior among Malaysian investors. A total of 400 questionnaires are distributed to bank institutions' investors. The survey design based on cross-sectional data is analyzed using the Partial Least Squares Structural Equation Model. The results indicate that information, market sentiment, experience, and national culture are positively related to herding behavior, while overconfidence has no effect. With this, the government should strengthen regulations to prevent the dissemination of misleading information. Moreover, investors are encouraged to overcome narrow thinking by expanding their understanding of different cultures when making investment decisions.

This study aims to investigate how different menu types trigger diners’ behavioral intentions in restaurants’ innovation diffusion from paper to digital menus.

Four menu types, namely, paper menus with text only, paper menus with text and images, digital menus that show text and images or text and video with self-service technological functionality, are designed to empirically examine a mental process through which perceived information quality, perceived food quality and perceived service quality influence diners’ behavioral intentions.

Based on the online survey data from 502 diners, results show that the menu design influences customers’ perceptions. The video-based digital menu is the most effective to generate diners’ behavioral intentions, followed by a paper menu with text and images.

This study contributes to the innovation diffusion theory and stimulus-organism-responses theory to encourage the joint use of auditory and visual channels for digital menu design in restaurants.

The authors confirm the digital transformation in menu design in restaurants. Restaurant diners are also prepared and comfortable with digital menus, especially in the postpandemic world.

本研究目的在于调查在餐厅从纸质菜单到数字菜单的创新扩散过程中, 不同菜单类型如何影响餐厅客人的行为意向。

通过设计并使用四种菜单类型, 分别为只有文本的纸质菜单、具有文本和图片的纸质菜单、显示文本和图片或文本和视频的数字菜单以及具有自助技术功能的数字菜单, 本研究以实证方法考察了感知信息质量、感知食品质量和感知服务质量如何影响餐厅客人的行为意向的心理过程。

根据对502名餐厅客人的在线调查数据显示, 菜单设计影响了客人的感知。基于视频的数字菜单是影响餐厅客人行为意向最有效的菜单类型, 其次是文本和图片的纸质菜单。

本研究表明应鼓励在餐厅数字菜单设计中同时使用听觉和视觉元素。因此, 为研究促进了创新扩散理论和刺激-有机体-反应理论的发展。

我们证实了数字菜单在餐厅菜单设计中的转型。餐厅客人, 尤其是在在后疫情时代, 已经准备好并愿意接受使用数字菜单。

Drawing on the mSERVQUAL model and spillover theory, this study aims to examine the mechanism through which food-ordering mobile app service quality influences users’ mobile app satisfaction, food satisfaction and repurchase intentions.

Online surveys were completed by 1,000 customers who used a food-ordering mobile app to order fast food on the day they completed the online survey. Structural equation modelling was then used to examine the proposed mechanism.

Results showed that the effects of food-ordering mobile app service quality on customer satisfaction (i.e. mobile app satisfaction and food satisfaction) and repurchase intention varied widely across service quality dimensions. Mobile app service quality had significant spillover effects on food satisfaction and repurchase intention.

Online food-delivery platforms should find the results insightful to better design their food-ordering mobile app. The findings can also assist restaurateurs and mobile payment companies with supporting the whole online food delivery process.

Rather than examining online food delivery service quality based on the service delivery process in the during-consumption stage or the service outcomes in the post-consumption stage, this study focused on the service quality in the pre-consumption stage to highlight the important role of online food delivery mobile apps. From a longitudinal perspective, this study drew on the associate network theory to explain the spillover effect of mobile app satisfaction in the pre-consumption stage on food satisfaction in the during-consumption stage and repurchase intention in the post-consumption stage.

When encountering novel technology, customers often use the term “cool” to express their thoughts; therefore, coolness has become crucial for launching service robots. However, research on the impact mechanism of “coolness” is lacking. This study explored the relationship between delight and behavioral intention regarding the coolness of service robots in the food and beverage industry while discussing the mediating roles of utilitarian and hedonic values.

Questionnaires were distributed online with links to the survey posted on restaurant discussion boards on Facebook and online community platforms such as Dcard. In total, 540 responses were deemed valid. The hypotheses were tested using the partial least squares structural equation modeling method.

The results indicate that coolness positively impacted both utilitarian and hedonic values and that both perceived values positively impacted delight. Moreover, coolness does not directly impact delight but must be mediated by perceived value to be effective.

Increasing customer perceptions of the coolness of service robots is recommended. Moreover, regarding customer revisits, utilitarian value services can delight customers more effectively than hedonic value services.

The stimulus-organism-response model was used to identify the relationships among coolness, perceived value, delight and behavioral intention. Moreover, the authors investigated the impact of coolness on utilitarian and hedonic values. These findings are significant for the development of smart restaurants and provide a critical reference for exploring service robots.

Given the regional heterogeneity of economic development, electricity consumption in various regions exhibits a discrepant growth pattern. The purpose of this study is to construct a grey system forecasting model with intelligent parameters for predicting provincial electricity consumption in China.

First, parameter optimization and structural expansion are simultaneously integrated into a unified grey system prediction framework, enhancing its adaptive capabilities. Second, by setting the minimum simulation percentage error as the optimization goal, the authors apply the particle swarm optimization (PSO) algorithm to search for the optimal grey generation order and background value coefficient. Third, to assess the performance across diverse power consumption systems, the authors use two electricity consumption cases and select eight other benchmark models to analyze the simulation and prediction errors. Further, the authors conduct simulations and trend predictions using data from all 31 provinces in China, analyzing and predicting the development trends in electricity consumption for each province from 2021 to 2026.

The study identifies significant heterogeneity in the development trends of electricity consumption systems among diverse provinces in China. The grey prediction model, optimized with multiple intelligent parameters, demonstrates superior adaptability and dynamic adjustment capabilities compared to traditional fixed-parameter models. Outperforming benchmark models across various evaluation indicators such as root mean square error (RMSE), average percentage error and Theil’s index, the new model establishes its robustness in predicting electricity system behavior.

Acknowledging the limitations of traditional grey prediction models in capturing diverse growth patterns under fixed-generation orders, single structures and unadjustable background values, this study proposes a fractional grey intelligent prediction model with multiple parameter optimization. By incorporating multiple parameter optimizations and structure expansion, it substantiates the model’s superiority in forecasting provincial electricity consumption.

Numerous biotechnology and pharmaceutical firms have undergone considerable changes and adapted to the challenge of developing sustainable products and services. However, few studies have explored the factors that contribute to the success of external innovation and value co-creation strategies adopted by biotechnology and pharmaceutical firms. The purpose of this study is to examine how biotechnology and pharmaceutical industries use value co-creation strategies to obtain external resources.

This study developed a conceptual framework based on the relevant literature. The study applied a resource-based approach, dynamic capability theory and a qualitative multiple-case study design to investigate several research questions; semi-structured interviews were conducted with representatives from 11 biotechnology/pharmaceutical firms in Taiwan, and the data extracted from the interview content were axially coded.

This study revealed that factors such as dynamic marketing capabilities and process optimization contributed to the success of the aforementioned strategies; several propositions were also developed on the basis of the literature review and coded data, thereby providing insights regarding the relative efficacy and propriety of various external innovation and value co-creation strategies and models in various situations and contexts. Firms and technology providers might enter a technology licensing agreement, establish a joint venture company; participate in a merger/acquisition depending on their size, research and development capabilities; or goals and time- and cost-related factors.

The main original contributions of this study are the proposed conceptual framework and the insights provided regarding the relative efficacy and propriety of different external innovation and value co-creation strategies and models in different situations and contexts.

The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to examine whether media richness (MR), human-system interaction (HSI) and human-human interaction (HHI) as technological feature antecedents to medical professionals’ learning engagement (LE) can affect their learning persistence (LP) in massive open online courses (MOOCs).

Sample data for this study were collected from medical professionals at six university-/medical university-affiliated hospitals in Taiwan. A total of 600 questionnaires were distributed, and 309 (51.5%) usable questionnaires were analyzed using structural equation modeling in this study.

This study certified that medical professionals’ perceived MR, HSI and HHI in MOOCs positively affected their emotional LE, cognitive LE and social LE elicited by MOOCs, which together explained their LP in MOOCs. The results support all proposed hypotheses and the research model accounts for 84.1% of the variance in medical professionals’ LP in MOOCs.

This study uses the S-O-R model as a theoretical base to construct medical professionals’ LP in MOOCs as a series of the psychological process, which is affected by MR and interaction (i.e. HSI and HHI). Noteworthily, three psychological constructs, emotional LE, cognitive LE and social LE, are adopted to represent medical professionals’ organisms of MOOCs adoption. To date, hedonic/utilitarian concepts are more commonly adopted as organisms in prior studies using the S-O-R model and psychological constructs have received lesser attention. Hence, this study enriches the S-O-R model into an invaluable context, and this study’s contribution on the application of capturing psychological constructs for completely explaining three types of technological features as external stimuli to medical professionals’ LP in MOOCs is well-documented.

This study aims to examine the scientific publications related to leadership research in hospitality from 2000 to 2021 by conducting a systematic review (qualitative) and to discuss implications for future research.

For the qualitative approach, the authors conduct an in-depth critique of major leadership theories using 167 articles indexed in the Web of Science Core Collection.

The findings show that transformational leadership, leader–member exchange and servant leadership are the most prominent leadership topics studied from 2000 to 2021, followed by abusive supervision, empowering leadership, ethical leadership and authentic leadership. A framework is presented highlighting the mediators, moderators, outcomes, sample and research designs used in each of these lines of leadership research. Moreover, 16 areas for further research are identified and discussed.

This review uncovers scholars’ general lack of regard for how the study of leadership might benefit from examining hospitality as a special and challenging context for leadership and business performance.

This study reviews and critically analyzes leadership research in hospitality using qualitative methods. Therefore, the authors believe this review is of great value to academics and practitioners because it synthesizes and analyzes the field and identifies important research opportunities.