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The purpose of this paper is to investigate the effect of the government's role in boosting the utilization of intelligent robot by considering government support policies along with various other factors, which are potentially influential. This type of investigation will contribute for developing a domestic robot infrastructure in Korea.

A structural equation model is used to investigate the relation among various factors that have a potential influence on robot utilization. In addition, the Robot Utilization Expectation Index of various user groups is developed. The results obtained from the proposed model are expected to provide important feedback information for productivity innovation at the level of both the individual user and the company.

According to the results, the robot function has the highest direct effect on the Robot Utilization Expectation, but excessive policies implemented simultaneously by the Korean Government are not effective on revitalization of the robot industry. It is interesting to note that government policy has the highest indirect effect on robot utilization expectation. Therefore, it is proposed that the government should act as a mediator and focus on fewer policies rather than enforcing various policies simultaneously by different organizations.

Although, a focused group consisting of those who are knowledgeable about intelligent robots is surveyed, a limitation to the paper lies in analyzing a relatively small data set. An extended survey with a larger data set remains for future study.

The paper includes implications, which contribute towards stimulating the robot industry in Korea.

The proposed model is expected to provide important information for productivity innovation at both the individual user and company levels.

This paper aims to find out the impact of seven important factors towards behavior intention on various health-care applications in India. The spectacular rise of uses of smart phones in India has introduced various mobile applications in the market. The mobile applications have become very useful and popular amongst the urban consumers due to several reasons such as reducing time, effort, money, etc. Health-care applications which are used in various smart phones are still in an infancy stage in India. Health-care applications have several advantages and facilities and consumers receive few alerts or suggestions for free. Though the health-care applications have various benefits for everyone, still people are less aware of the services they provide. Fewer studies have been done on this particular subject, and people may find the apps interesting if they understand the benefits of these applications.

This study aims to find out the impact of seven factors towards behavior intention on various health-care applications in India. The 331 samples have been chosen with the help of a structured questionnaire. The researcher has used stratified random sampling to collect the data for conducting the study, and the samples have been collected from four metro cities of India, namely, Kolkata, Mumbai, Delhi and Chennai. Exploratory factor analysis and multiple regression analysis have been conducted to find out the most influencing factor towards intention with SPSS v 21.

The result reveals that out of seven factors, perceived usefulness, enjoyment and time are the most influencing and significant factors towards utilization expectation. The other four variables, namely, cost, increased dependability, perceived ease of use and increased protection do not have a significant impact on the dependent variable. The paper has also revealed that marketers need to penetrate the market with some innovative marketing strategies. The findings of the study is providing the hint for implementing the strategies.

The study is unique in the context of a country like India where no such studies on this subject have been conducted before.

Technological advances regarding artificial intelligence (AI) are affecting the transport sector. Although fully autonomous delivery, or self-driving trucks, are not operating currently, various AI applications have become fixed components of cargo vehicles. Since many research approaches primarily concentrate on the technical aspects of assistance systems (ASs), the economic question of how to improve efficiency is seldom addressed. Therefore, the purpose of this paper is to apply an efficiency analysis to measure the performance of truck drivers supplying retail stores.

For this comparative study, 90 professional truck drivers in three groups are compared with (1) trucks without AS, (2) trucks with AS that cannot be turned off and (3) trucks with AS that can be turned off. First, we build a model investigating the impact of performance expectation, effort expectation, social influence and facilitating conditions on the behavioural intention to use AS. Second, we explore the impact of truck drivers' behavioural intention on actual technology use, misuse and disuse; operationalize these constructs; and merge them with our behavioural constructs to create one econometric model.

The human–AI system was found to be the most efficient. Additionally, behavioural intention to use ASs did not lead to actual usage in the AI-alone observation group, but did in the human–AI group. Several in-depth analyses showed that the AI-alone group used AS at a higher level than the human–AI group, but manipulations through, for example, kickdowns or manual break operations led to conscious overriding of the cruise control system and, consequently, to higher diesel consumption, higher variable costs and lower efficiency of transport logistical operations.

Efficiency analysis with data envelopment analysis is, by design, limited by the applied input and output factors.

This study represents one of the first quantitative efficiency analyses of the impact of digitalization on transport performance (i.e. truck driver efficiency). Furthermore, we build an econometric model combining behavioural aspects with actual technology usage in a real application scenario.

This study aims to analyze the effects of performance expectancy, effort expectancy, social influence and facilitating conditions on the behavioral intention of using mobile health applications, especially during and after the COVID-19 pandemic.

A survey was developed using an online survey platform and distributed to Indonesian consumers for three weeks, and 149 usable responses were obtained. The principal component analysis, linear regression and analysis of variance tests were performed to test the validity and reliability of the measurement model and the hypothesized relationships among constructs.

Surprisingly, unlike previous studies on IT adoption, the findings show that social influence has no significant impact on behavioral intention. Facilitating conditions have a very weak to almost no significant impact on behavioral intention to use mobile health applications.

This research is conducted during pandemic COVID-19 where using mobile health apps is a must. In the future this research can be expanded as comparison study after the pandemic COVID-19 stated.

The result implies that digital technologies adoption intention is strongly affected by performance expectancy and effort expectancy, with performance expectancy as the most significant predictor. Nonetheless, the interaction of performance expectancy, effort expectancy, social influence and facilitating conditions influences behavioral intention significantly. Therefore, social influence and facilitating conditions are still important even with very insignificant effects.

To improve consumers’ behavioral intention to use mobile health applications, application providers should promote mobile health applications as useful telemedicine tools by primarily focusing on the application performance and usage experience.

This paper aims to develop an understanding of key variables for designing and marketing healthcare services for immigrant consumers – widely considered a vulnerable consumer group.

Data collected from 277 participants was analyzed using ANOVA models and mean score comparisons.

Differences based on immigrant status and acculturation level are identified. Differences between immigrant acculturation levels based on service quality dimensions are also revealed.

This research indicates that acculturation-based studies are insightful and finds that immigrants’ service responses do not mirror those of native respondents in healthcare services.

This research highlights key nuances within immigrant populations that hold significant implications for service providers. Culturally appropriate service design and marketing can enhance service utilization by the target population.

This study focuses on the healthcare service experiences of immigrant populations and application of this information to service design.

The primary purpose of the study is to investigate college students' dining expectations and define the factors that shape their dining choices. In addition, the study investigates whether gender, ethnic origin, prior food and beverage working experience, spending habits and dining frequency influence students' dining expectations.

A quantitative questionnaire was developed and randomly administered to college students all over Cyprus. With the utilization of both descriptive and inferential statistics the authors addressed a number of research questions that aim to clarify college students' dining behaviour.

The research reliably measured college students' dining expectations and dining decisions in the Cyprus specific environment. Overall cleanliness, employees' attitude and quality of menu items were the most important factors influencing college students' dining choices. Reliability and responsiveness were ranked as the top dining expectations of college students. In addition, of value to industry practitioners, a number of statistically significant differences were revealed based on gender, spending habits, dining frequency, and prior food and beverage working experience.

The authors suggest an agenda for future academic research that will further clarify the dining habits of college students.

The findings have a practical relevance to food and beverage marketers who wish to capture the attention of this significant market segment. The research recognised the market's potential, in addition of revealing major differences between college students in a number of dining‐related factors with specific marketing implications.

It is the first time that a scientific study has investigated college students' dining expectations in Cyprus. The results have practical implications for both academic scholars and food and beverage practitioners.

The purpose of this paper is to examine the impact of radio frequency identification (RFID) technology utilization in manufacturing firms on manufacturing efficiency and effectiveness.

Using systems theory as a basis, a RFID utilization and outcome(s) performance model was developed from the literature. Data from a sample of 155 manufacturers were collected and the model was assessed using a structural equation methodology.

Findings indicate that utilization of RFID technology leads to improved manufacturing efficiency and manufacturing effectiveness. Improvements in efficiency lead directly to improved organizational performance, and improvements in effectiveness lead directly to improved supply chain performance.

Data were collected during the growth stage of RFID technology adoption and were only collected from firms in the manufacturing sector. Results should be interpreted with these limitations in mind.

The implementation of RFID technology can result in improved manufacturing efficiency and effectiveness. Practitioners considering adoption of the technology should fully account for these potential efficiency and effectiveness related benefits when determining the justification for adoption of this technology.

The paper describes one of the first empirically‐based studies investigating the impact of RFID technology implementation on supply chain and organizational performance in manufacturing organizations.

Reports the results of a field study on managerial decision making and competence utilization in Chinese enterprises. The results showed that the participative decision making had positive effects on both morale and decision quality and that the decision skill utilization had a very close relationship with job satisfaction. It also demonstrated that the measure of influence/power‐sharing was an appropriate indicator for decision‐making patterns in the Chinese circumstances. Discusses implications of the results and proposes a process model of managerial decision making.

The paper's aim is to theorize and assess a structural model that incorporates radio frequency identification (RFID) technology utilization and supply chain information sharing as antecedents to supply chain performance.

Data from a sample of 155 manufacturing sector and service sector organizations were collected and the model was assessed following a structural equation methodology.

RFID technology utilization does not directly impact supply chain performance. Adoption of RFID technology, however, leads to improved information sharing among supply chain members, which in turn leads to improved supply chain performance.

RFID technology utilization is in the introductory and growth stages of the technology utilization life cycle. Interpretation of the results should be tempered in light of this early stage of adoption.

Practitioners can expect improved customer satisfaction through the implementation of RFID technology and the information sharing that the technology facilitates.

The study offers empirical support for the adoption of RFID technology within an enterprise resource planning context for the purpose of improving supply chain performance.

High-Performance Work Systems (HPWS) are viewed as strategic levers to a firm’s core competencies’ sustainability and continuous competitive advantage. The purpose of this paper is to explore what factors facilitate HPWS utilization, with a particular focus on the extent to which social capital (SC) derived from buyer-supplier relationships functions as a communication channel to spread effective HPWS implementation.

The authors propose a model of HPWS in which external SC not only favors the use of HPWS but also moderates the incidence of other common facilitators such as technology and flexibility. The study uses data from Spanish manufacturing industry.

Firms yielding external SC use HPWS more intensely, and the effect of technology constituents on HPWS utilization is contingent on SC accumulation. The findings are consistent with the existing HR literature on the subject but broaden its perspective by analyzing a specific pattern of SC and its pivotal role in the HPWS utilization process.

The cross-sectional nature of the database leaves open the possibility of causality relationship exploration between the variables of interest, which means that any causal interpretation should be cautious and properly motivated. The study is conducted in the Spanish manufacturing industry context, hence aims to generalize its results by explaining the logic behind the coexistence of HPWS and SC on a same conceptual level. This should be carefully treated and could be further strengthened by other country-level research. The approach does not consider the internal synergic mechanisms and the integration of HR practices.

The paper reveals the importance of inter-organizational SC in the Spanish manufacturing industry by showing how its embodiment in buyer-supplier relationships may allow firms to better understand the context in which HPWS are more likely to be useful.

The impact of social relationships on effective human resource management practices is highlighted.

The authors explore the factors that facilitate HPWS utilization, with a particular focus on the extent to which SC derived from buyer-supplier relationships functions as a communication channel to spread effective HPWS implementation.