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This study aims to investigate how companies’ understanding of the business network influences the creation of value in business-to-business relationships. The authors do this by analysing dimensions in actors’ “network pictures” and illustrating how value perception and network understanding influence actors’ mutual effort to create value. Approaching relationship value from the point of actors’ cognitive understanding of their business network has so far been largely overlooked in relationship value research.

This study applies a qualitative case study methodology whereby dyadic data from a well-established business-to-business relationship is collected from 18 company representatives through personal interviews and group interviews supplemented by participant observations and company data.

The findings contribute with new insight into how companies’ understanding of their surrounding network influence (facilitates or limits) relationship value creation. The authors find that companies continuously reflect on changes in their networks and the related changes in partners’ value perceptions. Through value articulations, companies seek to explicitly express their value perception. Value reflections and value articulations create a dynamic process formed not only by the individual actor but also through their relationship and engagement in their network environment. This requires companies to develop their networking capabilities.

This paper presents findings, insights and contributions limited to a case study of a particular business relationship within an industrial setting. Although the findings and contributions are valid and in line with the criteria for rigorous qualitative research, the authors advocate and call for additional studies that investigate relationships value creation and address the interplay between actors’ network understanding and their actions and behaviour. One way to approach this would be to test the four propositions derived and presented as part of the present study.

The findings imply that management needs to be aware not only of the value created and delivered to a specific partner but also of how the partner’s understanding of the wider network will influence the value delivering and capturing process.

This study contributes to the growing literature on relationship value creation by outlining a dynamic process where relationship partners reflect upon and articulate value. Such activities are influenced by the partners’ network understanding and form the basis of the mutual relationship value creation effort. The findings also contribute to the network pictures literature by emphasizing insights into the formation of value perceptions through actors’ understanding of their surrounding networks.

This paper aims first to describe the most prevalent teachers’ and students’ behaviors in synchronous online classes in emergency remote teaching; second, to discern behavior profiles and third, to investigate what features explain the observed behaviors.

An adapted COPUS observation protocol was employed to observe 292 online classes from 146 higher education teachers.

The most prevalent behaviors were: Presenting for teachers and Receiving for students, followed by Teachers Guiding and Students Talking to Class. Furthermore, cluster analysis showed two groups: Traditional and Interactive. The variables that better explained belonging to the Interactive lecture group were disciplinary area – social sciences and humanities –and teaching in technical institutions.

In a context where higher education institutions intend to project the lessons learned into post-pandemic learning experiences, this study provides observational evidence to realize the full potential expected from online and blended teaching and learning.

Despite the prevalence of synchronous online lectures during COVID-19, there is a paucity of observational studies on the actual behaviors that occurred in this context. Most research has been based on surveys and interviews. This study addresses this gap.

This study investigates human behavior, specifically attitude and anxiety, toward humanoid service robots in a hotel business environment.

The researcher adopted direct observations and interviews to complete the study. Visitors of Henn-na Hotel were observed and their spatial distance from the robots, along with verbal and non-verbal behavior, was recorded. The researcher then invited the observed hotel guests to participate in a short interview.

Most visitors showed a positive attitude towards the robot. More than half of the visitors offered compliments when they first saw the robot receptionists although they hesitated and maintained a distance from them. Hotel guests were also disappointed with the low human–robot interaction (HRI). As the role of robots in hotels currently remains at the presentation level, a comprehensive assessment of their interactive ability is lacking.

This study contributes to the HRI theory by confirming that people may treat robots as human strangers when they first see them. When a robot's face is more realistic, people expect it to behave like an actual human being. However, as the sample size of this study was small and all visitors were Asian, the researcher cannot generalize the results to the wider population.

Current robot receptionist has limited interaction ability. Hotel practitioners could learn about hotel guests' behavior and expectation towards android robots to enhance satisfaction and reduce disappointment.

Prior robot research has used questionnaires to investigate perceptions and usage intention, but this study collected on-site data and directly observed people's attitude toward robot staff in an actual business environment.

The development of the digital age has made data and information more transparent, enhancing the strategic perspectives of both buyers (strategic waiting) and sellers (price fluctuations) in their decision-making. This research investigates the optimal dynamic pricing strategy of the content product developer in relation to their consideration of consumer fairness concerns to elucidate the impact of consumer fairness concerns on the dynamic pricing strategy of the developer.

This paper assumes that monopolistic content developers implement a dynamic pricing strategy for the content product. Through constructing a two-period dynamic pricing game model, this research investigates the optimal decisions of the content developer, contingent upon their consideration or disregard of consumer fairness concerns. In the extension section, the authors additionally account for the influence of myopic consumers on these optimal decisions.

Our findings reveal that the degree of consumer fairness concerns significantly influences the developer’s optimal dynamic pricing decision. When a developer offers content products with lower depth, there is a propensity for the developer to refrain from incorporating consumer fairness concerns into a dynamic pricing strategy. Conversely, in cases where the developer offers a high-depth content product, consumer fairness concerns benefit the developer. Furthermore, our analysis reveals a consistent benefit for the developer from the inclusion of myopic consumers.

Few studies have delved into the conjoined influence of consumer fairness concerns and strategic behavior on dynamic pricing strategy. Our findings indicate that consumer fairness concerns can enhance the efficiency of the value chain for content products under specific conditions. This paper not only enriches the existing literature on dynamic pricing by incorporating consumer fairness concerns theoretically but also offers practical insights. The outcomes of this research can guide content product developers in devising optimal dynamic pricing strategies.

Occupant behavior can lead to considerable uncertainties in thermal comfort and air quality within buildings. To tackle this challenge, the use of probabilistic controls to simulate occupant behavior has emerged as a potential solution. This study seeks to analyze the performance of free-running households by examining adaptive thermal comfort and CO2 concentration, both crucial variables in indoor air quality. The investigation of indoor environment dynamics caused by the occupants' behavior, especially after the COVID-19 pandemic, became increasingly important. Specifically, it investigates 13 distinct window and shading control strategies in courtyard houses to identify the factors that prompt occupants to interact with shading and windows and determine which control approach effectively minimizes the performance gap.

This paper compares commonly used deterministic and probabilistic control functions and their effects on occupant comfort and indoor air quality in four zones surrounding a courtyard. The zones are differentiated by windows facing the courtyard. The study utilizes the energy management system (EMS) functionality of EnergyPlus within an algorithmic interface called Ladybug Tools. By modifying geometrical dimensions, orientation, window-to-wall ratio (WWR) and window operable fraction, a total of 465 cases are analyzed to identify effective control scenarios. According to the literature, these factors were selected because of their potential significant impact on occupants’ thermal comfort and indoor air quality, in addition to the natural ventilation flow rate. Additionally, the Random Forest algorithm is employed to estimate the individual impact of each control scenario on indoor thermal comfort and air quality metrics, including operative temperature and CO2 concentration.

The findings of the study confirmed that both deterministic and probabilistic window control algorithms were effective in reducing thermal discomfort hours, with reductions of 56.7 and 41.1%, respectively. Deterministic shading controls resulted in a reduction of 18.5%. Implementing the window control strategies led to a significant decrease of 87.8% in indoor CO2 concentration. The sensitivity analysis revealed that outdoor temperature exhibited the strongest positive correlation with indoor operative temperature while showing a negative correlation with indoor CO2 concentration. Furthermore, zone orientation and length were identified as the most influential design variables in achieving the desired performance outcomes.

It’s important to acknowledge the limitations of this study. Firstly, the potential impact of air circulation through the central zone was not considered. Secondly, the investigated control scenarios may have different impacts on air-conditioned buildings, especially when considering energy consumption. Thirdly, the study heavily relied on simulation tools and algorithms, which may limit its real-world applicability. The accuracy of the simulations depends on the quality of the input data and the assumptions made in the models. Fourthly, the case study is hypothetical in nature to be able to compare different control scenarios and their implications. Lastly, the comparative analysis was limited to a specific climate, which may restrict the generalizability of the findings in different climates.

Occupant behavior represents a significant source of uncertainty, particularly during the early stages of design. This study aims to offer a comparative analysis of various deterministic and probabilistic control scenarios that are based on occupant behavior. The study evaluates the effectiveness and validity of these proposed control scenarios, providing valuable insights for design decision-making.

This study uses a comprehensive theoretical framework that combines social cognitive theory and neighborhood effect to investigate the influence of neighborhood effects on farmers’ outcome expectations, observational learning and self-efficacy. This study aims is to analyze the mechanisms that underlie the adoption of social media by farmers for knowledge exchange in the agricultural context. Specifically, this research explores the role of neighborhood effects, outcome expectations, observational learning and self-efficacy in shaping farmers’ decision-making process regarding the use of social media platforms for exchanging agricultural knowledge.

The study data was collected through a sample survey conducted among 570 agricultural households residing in the provinces of Thai Nguyen, Cao Bang, Bac Kan and Phu Tho, located in the northern region of Vietnam. To analyze the data, structural equation modeling was used as the statistical technique of choice.

The findings of the study indicate a significant influence of neighborhood effects on outcome expectations, observational learning and self-efficacy. These factors, derived from social cognitive theory, also exhibit a positive association with farmers’ adoption of social media for knowledge exchange. Additionally, the study highlights that neighborhood contribute to a favorable adoption of social media among farmers via outcome expectations, observational learning, and self-efficacy.

The study is limited in examining farmers’ social media adoption for agriculture knowledge exchange in Northern mountainous area of Vietnam. This study could be replicated across various regions or nations, providing comparative insights into the adoption of social media among farmers for knowledge exchange.

The study findings suggest practical and innovative means to promote farmers’ social media adoption for agriculture knowledge exchange.

This study presents a pioneering approach by integrating social cognitive theory and neighborhood effect to elucidate the factors influencing farmers’ adoption of social media for the purpose of agriculture knowledge exchange.

This study is designed to bridge a gap in the existing leadership communication literature by delving into lesser-explored facets of the field. It particularly concentrates on investigating how the verbal aggressiveness of supervisors influences various aspects of the workplace, including workplace emotional culture, the quality of employee–organization relationships (EORs) and the prevalence of counterproductive work behaviors (CWB).

This study employed a quantitative research design to investigate the impact of supervisors' verbal aggressiveness on employee and organizational outcomes. The data were collected from 392 full-time employees across various organizations and industries in the USA using a self-report questionnaire. The researchers used structural equation modeling (SEM) to analyze the data and test hypotheses.

The findings of this study showed that supervisors' verbal aggressiveness had a significant positive association with negative emotional culture and employee CWB. However, it had no direct impact on employee–organization relationships. The effect of supervisor verbal aggressiveness on employee CWB was found to be mediated by a negative team-level emotional culture.

This study advances the literature on leadership communication by highlighting the detrimental influence of the dark side of leadership communication. More specifically, by identifying negative emotional culture and employee CWB as the direct outcomes of supervisor verbal aggressiveness, the authors add to the existing theoretical knowledge on verbal aggressiveness in the workplace. Additionally, this study provides empirical evidence of the impact of a negative emotional culture on eliciting employees' CWBs and diminishing relationship quality, adding to the body of knowledge on why managing emotional culture is crucial for organizations and workgroups.

This paper aims to introduce the experience-dominant (Ex-D) logic model, which synthesizes the creation, perceptions and outcomes of Ex-D logic. It is designed to offer valuable insights for strategic managerial applications and future research directions.

Employing a qualitative approach by using eight selected product launch events from reviewed 100 event videos and 55 in-depth interviews with industrial managers to develop an Ex-D logic model, and data were coded and analysed via NVivo.

Results show that the firm’s Ex-D logic is operationalized as the mentalizing of the three types of customer needs (service competence, hedonic excitations and meaning making), the materializing of three types of customer experiences and customer journeys (service experience, hedonic experience and brand experience) and the moderating of three types of customer values (service values, hedonic values and brand values).

This study has implications for adding new insights into existing theory on dominant logic and customer experience management and also offers actionable recommendations for managerial applications.

This study sheds light on the importance of Ex-D logic from a strategic point of view and provides an organic view of the firm. It distinguishes firm perspective from customer perspective, firm experience from customer experience and firm journey from consumer journey.

Military values/virtues are a subset of ethical values. The purpose of this study is to examine the effect of military virtues on job performance, either directly, or indirectly through mediation by, loyalty, patience, respect, employee engagement, job performance, military ethics, courage, self-discipline, caring, military virtue, Sri Lanka Air Force (SLAF) employee engagement.

Military virtues were conceptualized as a collective construct, consisting of loyalty, courage, patience, respect, self-discipline and caring. Using a sample of 254 military officers in the SLAF, the authors measured the effect of military virtues on job performance. The first model was a direct measurement of the influence of military virtues on job performance. The second model measured the influence of military virtues on employee engagement, followed by measurement of the influence of employee engagement on job performance. Structural equation modeling was used in data analysis.

Both direct effects and mediated effects of military virtues on job performance were significant. However, the direct effect was stronger, suggesting that military virtues in and of themselves resulted in superior performance, more effectively, than by first increasing employee engagement with the task or the organization.

This may be an initial empirical examination of the effects of military virtues on job performance.

This study aims to explore and understand the challenges and opportunities presented by the rising demand for organic products in the context of toddy consumption and marketing.

This research examines consumer behaviour and decision-making patterns using decision tree analysis. A survey questionnaire based on established theories was distributed to individuals above the legal drinking age of 23 in Kerala, India, using purposive and random sampling.

The study found that people's fondness for toddy shop food plays a crucial role in their food choices. When the fondness is low, subjective norms can override personal preferences. But when the fondness is high, individual perceptions take precedence.

Using machine learning techniques, we created a compass to guide marketing strategies and cultural preservation efforts in toddy shops by considering the complex factors that influence consumer decisions.