Microblogging,friendship maintenance,and life satisfaction among university students: The mediatory role of online self-disclosure

Despite a substantial literature suggests that computer-mediated communication impact individuals’ various psychosocial factors, relatively few studies have elucidated the underlying mechanism behind these associations. Building upon self-disclosure theory and previous studies, the principal purpose of this present research is to systematically explore the relationships among microblog utilization, online self-disclosure, friendship maintenance, and perceived life satisfaction. A web-based survey was implemented using a total of 426 university students in Northwestern China. Structural equation modeling reveals that intensity of microblog use is positively associated with these students’ friendship maintenance and life satisfaction. Additionally, online self-disclosure plays the crucial mediatory role in the relationships between microblog use, quality of relationships, and gratification with life. The results imply that as microbloggers disclosure their inner thoughts or emotional states with other users online, they could foster their friendship maintenance and obtain greater life satisfaction. However, contrary to the expectation, students’ friendship maintenance is not discovered to be a significant predictor of the sense of life satisfaction in the online environment. Overall, these obtained outcomes of the empirical work could offer new insights into the deep comprehending of the social psychological process of microblogging among younger generation in the new media context.     

Mapping gender and marital roles on customer delight by value perception for mobile technology in India

The Indian telephony industry is a diverse platform for product and service in customer value perception. The present study organizes and synthesizes the varied research streams for developing a customer value delight (CVD) framework for marketing decisions like segmentation and targeting. The conceptual framework is developed by using ten-value predictor variables and customer delight through divergent viewpoints identified from previous studies. The significance of the segregation proposition is tested through discriminant analysis in three different dimension runs i.e. delight, gender, and marital category. The scholarship behind the study provides insight into an imperative issue of segregating customer delight by perceived value predictors in categories. The perceptual mapping and vector magnitude analysis of value predictors were performed to club customers in two categories of Mid-Town (low/moderate delight) and Extremes (high delight). The analysis rigorously supports the discriminating power of perceived price, perceived benefit, and self-congruity. The salience of study unlocks psychographic and demographic perceptual maps of customer delight with its perceived value predictors for strategic and tactful planning in the mobile industry.     

Domestic demand-side response with heat pumps: controls and tariffs

ABSTRACT

Electric heat pumps feature prominently in projected energy transitions in the UK and elsewhere. Owing to their high electricity consumption, heat pumps are viewed as important targets for demand-side response (DSR). Findings are presented from a field trial of a new control system that aims to optimize heat pump performance, including under time-varying tariff conditions. The trial involved monitoring 76 properties with heat pumps, but without dedicated heat storage; 31 of these received the control system. Interviews were conducted with a subsample of 12 participants. The controller successfully evened out electricity demand over the day (reducing the evening peak), but this was associated with increased late night and daytime temperatures. Interview participants reported some disturbance owing to overnight heating and noise, as well as usability issues with the controller interface and hardware. These issues present risks to the future acceptability of such systems. While the system delivered short-term demand reductions successfully, longer-term demand shifting risked causing unacceptable disturbance to occupants. Future control systems could overcome some of the issues identified in this pioneering trial through more effective zoning, using temperature caps or installing dedicated heat storage, but these may either limit the available flexibility or be challenging to achieve.     

Does thermal control improve visual satisfaction? Interactions between occupants’ self-perceived control,visual, thermal,and overall satisfaction

Occupants’ satisfaction had been researched independently related to thermal and visual stimuli for many decades showing among others the influence of self-perceived control. Few studies revealed interactions between thermal and visual stimuli affecting occupant satisfaction. In addition, studies including interactions between thermal and visual stimuli are lacking different control scenarios. This study focused on the effects of thermal and visual factors, their interaction, seasonal influences, and the degree of self-perceived control on overall, thermal, and visual satisfaction. A repeated-measures laboratory study with 61 participants running over two years and a total of 986 participant sessions was conducted. Mixed model analyses with overall satisfaction as outcome variable revealed that thermal satisfaction and visual satisfaction are the most important predictors for overall satisfaction with the indoor environment. Self-perceived thermal control served as moderator between thermal satisfaction and overall satisfaction. Season had slight influence on overall satisfaction. Random effects explained the highest amount of variance, indicating that intra- and interindividual differences in the ratings of satisfaction are more prevalent than study condition. Future building design and operation plans aiming at a high level of occupant satisfaction should consider personal control opportunities and take into account the moderating effect of control opportunities in multimodal interactions.     

Integrated rough VIKOR for customer-involved design concept evaluation combining with customers’ preferences and designers’ perceptions

Customer-involved design concept evaluation (DCE) allows customers to take part in evaluating the design alternatives to get more popular design concept. Traditional customer-involved DCE methods still focus on the collection of customer responses and only consider cost and benefit characteristics of design criteria in multi-criteria decision-making (MCDM) based evaluation process. Few studies have customized the decision-making algorithms specifically aimed at customers’ preferences. This paper further explores the customers’ influences in the early stages of the product design development, and proposes a new rough number based MCDM model (i.e., VIKOR) incorporating customers’ preferences for design specifications along with designers’ perceptions for the characteristics of design criteria (cost and benefit) to perform concept evaluation under subjective environment, and this proposed method is named as integrated rough VIKOR (IR-VIKOR). The objective of this study is to identify the best design concept which maximizes the satisfactions of expectations from most customers as well as conforms to the characteristics of design criteria. Firstly, Shannon entropy is used to obtain the weightings and relative importance ratings of design criteria from the customers’ preferences. Secondly, the customers’ preferences for design attribute values, the importance ratings of design criteria and the characteristics of design criteria are combined together to define the ideal solutions to calculate the rough evaluation index of each design alternative in IR-VIKOR, and finally the ranking result is provided by IR-VIKOR to determine the best design concept. A practical design example is introduced to illustrate the evaluation process of this proposed method, and the empirical comparisons are further carried out to validate its superiority for DCE. Through the sensitivity analysis experiments including i) inside IR-VIKOR, and ii) between IR-VIKOR and other classical MCDM methods, the proposed method is proved to be a reliable and feasible customer-involved DCE approach.     

Mapping Sentiments to Themes of Customer reactions on Social Media during a Security Hack: A Justice Theory Perspective

As social media continues to transform firm–customer interactions, firms must leverage customer reactions to generate actionable insights, especially in contexts (e.g., crisis events) where customer reactions are critical. Using the justice theory, we categorize customer reactions of two firms, Home Depot and Target, during the time-frame of a security hack to understand key themes/topics. We then map the themes/topics to customer sentiments in those reactions. We found that customers associate justice with simple procedures than the experience of dealing with the firm. In addition, it is critical for firms to carefully assess and control customer sentiments on social media during crisis events.     

Effects of risks on the performance of business process outsourcing projects: The moderating roles of knowledge management capabilities

Although business process outsourcing (BPO) can reduce cost and enhance the competitiveness of firms, the implementation of BPO projects is unsatisfactory. By integrating knowledge management capability theory and risk-based view, we develop a model of how different types of BPO risks affect project satisfaction and how knowledge management capability changes the influences of BPO risks. A survey of 121 BPO projects was conducted among BPO client department manager and project manager through a pairwise design. Empirical evidence reveals that social system, technical system, and project management risks negatively affect BPO project satisfaction. However, cultural, technological, and structural levels of knowledge management capabilities weaken the negative risk effects of social system, technical system, and project management, respectively. Different types of risks and knowledge management capabilities should be matched to achieve effective risk management.     

Customer satisfaction and loyalty analysis with classification algorithms and Structural Equation Modeling

Businesses can maintain their effectiveness as long as they have satisfied and loyal customers. Customer relationship management provides significant advantages for companies especially in gaining competitiveness. In order to reach these objectives primarily companies need to identify and analyze their customers. In this respect, effective communication and commitment to customers and changing market conditions is of great importance to increase the level of satisfaction and loyalty. To evaluate this situation, level of customer satisfaction and loyalty should be measured correctly with a comprehensive approach. In this study, customers are investigated in 4 main groups according to their level of satisfaction and loyalty with a criteria and group based analysis with a new method. We use classification algorithms in WEKA programming software and Structural Equation Modeling (SEM) with LISREL tools together to analyze the effect of each satisfaction and loyalty criteria in a satisfaction–loyalty matrix and extend the customer satisfaction and loyalty post-analysis research bridging the gap in this field of research. To convert developed conceptual thought to experimental study, white goods industry is exemplified. 15 criteria are used for evaluation in 4 customer groups and a satisfaction–loyalty survey developed by experts is applied to 200 customers with face-to-face interviews. As a result of the study, a customer and criteria grouping method is created with high performance classification methods and good fit structural models. In addition, results are evaluated for developing a customer strategy improvement tool considering method outcomes.     

Customer satisfaction in dynamic vehicle routing problem with time windows

The dynamic vehicle routing and scheduling problem is a well-known complex combinatorial optimization problem that drew significant attention over the past few years. This paper presents a novel algorithm introducing a new strategy to integrate anticipated future visit requests during plan generation, aimed at explicitly improving customer satisfaction. An evaluation of the proposed strategy is performed using a hybrid genetic algorithm previously designed for the dynamic vehicle problem with time windows that we modified to capture customer satisfaction over multiple visits. Simulations compare the value of the revisited algorithm exploiting the new strategy, clearly demonstrating its impact on customer satisfaction level.