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People can easily track and understand their usage pattern for any content (e.g. movies, games) or service (e.g. card payment, cell phone usage) by using technologies such as the internet and smart phones. When consumers evaluate their past consumption patterns, they may experience two different kinds of regret: content-based or monetary-based. The purpose of this paper is to propose that perceived self-control, defined as the extent to which people believe they can control their usage, plays a moderating role in the tariff-choice process (flatrate vs pay-per-use) for two types of content: vice-based and virtue-based.

Two laboratory experiments were designed to test the hypotheses. There were a total of 200 participants (86 for Experiment 1 and 114 for Experiment 2) who completed the entire experimental process (i.e. stimulus exposure, questionnaire reporting, dependent variable measurement, manipulation of the independent variables, and control checks).

The results of this research provide evidence supporting the role of perceived self-control in tariff preference by showing that preference varies between flat-rate and pay-per-use tariff options. Specifically, virtue-based content users were more likely to prefer the pay-per-use tariff when their perceived self-control was low vs when it was high. In contrast, vice-based content users were more likely to prefer the flat-rate tariff when their perceived self-control was low vs when it was high.

There are three contributions of the present research. First, the authors investigated the effect of content type on tariff preference. Second, the authors suggest that there is a moderating effect of perceived self-control on tariff preference. Third, this study revealed the factors affecting consumers’ perceived self-control.

This paper aims to investigate the mechanisms through which social media news consumption across different platforms leads to opinion polarization in society. To this end, the authors draw from cultivation theory to examine whether social media news consumption imparts a mainstreaming or resonance effect. Media consumption imparts a mainstreaming effect if frequent users, regardless of their social identity, develop homogenous attitudes about issues, whereas resonance is at play if there is a differing cultivation effect on various social groups depending on their relatability of life experiences.

The authors conduct the study in the developing context of India, using a population survey dataset from 2019. Regression-based mediation and moderation analyses were carried out to test the hypotheses.

The findings reveal that resonance is the most prominent mechanism through which social media news consumption cultivates opinion polarization, contrary to the mainstreaming effect imparted by television. Further, WhatsApp use was found to strengthen the polarizing effect of overall social media news consumption, while YouTube use weakened the cultivation of polarization.

The paper unearths how social media news consumption influences the opinion polarization of various social groups differently. The authors also find the differential effect of specific platform use. These findings have the potential to inform policymakers and developers about how to mitigate the detrimental effects of platform-based political persuasion.

This study offers significant contributions. First, the authors explain social media-induced polarization using the novel theoretical lens of cultivation. Second, the authors find that social media and television news consumption differ in their polarizing effects. Third, the authors find that while WhatsApp use amplifies the polarizing effect of social media news consumption, YouTube use weakens it.

The purpose of this paper is to provide librarians with an approach to weeding, which reduces librarians' fears and concerns of withdrawing books from an academic collection.

The paper takes the form of a case study.

The paper outlines specific steps for implementing a weeding project, including developing criteria and procedures, garnering the support of administration, building librarian confidence in performing weeding, and encouraging teaching faculty involvement.

The paper provides insights into the nature of the concerns and fears librarians face in weeding an academic library collection, and offers suggestions on how to build confidence and support for weeding among both librarians and academic faculty.

The purpose of this paper is to discuss and assess the structural characteristics (conceptual utility) of the most popular classification and predictive techniques employed in customer relationship management and customer scoring and to evaluate their classification and predictive precision.

A sample of customers' credit rating and socio‐demographic profiles are employed to evaluate the analytic and classification properties of discriminant analysis, binary logistic regression, artificial neural networks, C5 algorithm, and regression trees employing Chi‐squared Automatic Interaction Detector (CHAID).

With regards to interpretability and the conceptual utility of the parameters generated by the five techniques, logistic regression provides easily interpretable parameters through its logit. The logits can be interpreted in the same way as regression slopes. In addition, the logits can be converted to odds providing a common sense evaluation of the relative importance of each independent variable. Finally, the technique provides robust statistical tests to evaluate the model parameters. Finally, both CHAID and the C5 algorithm provide visual tools (regression tree) and semantic rules (rule set for classification) to facilitate the interpretation of the model parameters. These can be highly desirable properties when the researcher attempts to explain the conceptual and operational foundations of the model.

Most treatments of complex classification procedures have been undertaken idiosyncratically, that is, evaluating only one technique. This paper evaluates and compares the conceptual utility and predictive precision of five different classification techniques on a moderate sample size and provides clear guidelines in technique selection when undertaking customer scoring and classification.

In addition to instrumental assumptions, behavioural researchers suggest the study of individual traits such as personal innovativeness (PI), users’ satisfaction and other theoretical beliefs for example quality and general usage patterns as the latent determinants of early and post-adoptions of technological innovations. In the context of Higher Education Commission digital library of Pakistan, the purpose of this paper is to examine the relationship of PI, quality of digital resources and generic usability of digital libraries (DL) with users’ satisfaction.

To guide the conceptual model of this study, five hypothesized relationships were formulated. Adopting a quantitative approach, snowball sampling techniques were used. A total of 464 users of DL enrolled in different programs of study in the universities of Pakistan participated and responded to the survey. For data analyses, partial least squares, a method in the structural equation modeling was used.

Analyses reveal positive and strong relationships of PI, quality of digital resources and generic usability of DL with users’ satisfaction. Thus, the findings of this study established personal traits as the significant determinants of intention to adopt DL.

The decision of effective adoption is manipulated by the extent of users’ willing (PI), level of satisfaction, the image of quality and users’ past experience with the use of related innovations. Thus, librarians in addition to the system features should also focus on individual characteristics and quality of resources that probably influence adequate adoption of DL.

In the Pakistani context, this study is the first attempt that examined the relationship of PI, the usability of DL and quality of digital resources with users’ satisfaction. Research model of this study can be used in future research. Also, this study extended the scope of theories of adoption towards DL.

Noting that accurate information needs overlay the entire intelligence cycle from planning to reporting, the authors propose a new concept to fine‐tune the process of electronically gathering information. Since most tools are nondiscriminatory in information gathering, a new concept is needed to assist managers at all levels of the organization. The proposed multi‐class interest profile (M‐CLIP) provides the capability of expanding the representation of interests to reflect the assorted areas that make up a manager’s information needs. The M‐CLIP covers project, organizational, and industry class interest areas. Each area is customizable to make the search pertinent to the user while considering the need for both recall and precision. Supporting features, such as profile expansion, and fine‐tuning are also considered.

Recently the advances in wireless communication technology and the popularity of portable computers have rendered mobile computing environments from which mobile users with battery‐operated palmtops can access the information via wireless channels, without space and time restriction. In mobile computing environments, mobile users cache the data items to use the bandwidth efficiently and improve the response time of mobile transactions. If the data items cached in mobile users are updated at the server, the server broadcasts an invalidation report for maintaining the cache consistency of mobile users. However, this method has an obstacle that does not guarantee the serializable execution of mobile transactions. The purpose of this paper is to propose the four types of reports for mobile transaction (FTR‐MT) method for ensuring the serializable execution of mobile transactions.

The paper describes the FTR‐MT method, which is composed of four types of algorithms, e.g. group report composition algorithm, immediate commit decision algorithm, cache consistency algorithm, and disconnection cache consistency algorithm. FTR‐MT method for improving the response time of mobile transactions makes a commit decision by using the four types of reports.

With the FTR‐MT method, mobile users can make a commit decision by using the four types of reports. The response time of mobile transactions can be reduced. Furthermore, the FTR‐MT method can improve the cache efficiency in the case that the disconnection of mobile users is longer than the broadcast interval of the window report.

This paper proposes a new method for guaranteeing the serializable execution of mobile transactions, called FTR‐MT, using four types of reports. Also, it can prevent the entire cache dropping, even though the disconnection of a mobile host is longer than the broadcast interval of a window report. Through the analytical model, this method is felt to be superior to other methods, in terms of the average response time and the commit rate of mobile transactions, and bandwidth usage.

The purpose of the study is to develop a structural and a predictive model of the future purchase behavior of the consumers from value, quality and satisfaction and also finding the role of consumer loyalty in the above-mentioned model.

Based on survey and purchase data of a sample of 235 respondents, the authors have used structural equation modeling to develop a structural model and three-stage least square regression to develop and validate the predictive model.

In the structural model, the authors found that perceived service quality and network quality leads to customer satisfaction which also leads to loyalty intentions. However, neither past purchase behavior nor loyalty has significant predictive power to predict future usage. But the interaction effect of loyalty and past purchase predicts future purchase significantly.

The study went beyond structural model and developed a behavioral predictive model which can overcome self-reporting bias. Also, the study focused on the moderating role of loyalty in predicting future purchase quantity, thus contributing toward the theoretical understanding of the effects of loyalty.

Other than providing a forecasting model, the study helps the service managers to understand the importance of the relational constructs than the tangible constructs. Moreover, it also suggests optimally target the big buyers through the loyalty programs to ensure higher future revenues.

The study provides new insight on the impact of loyalty intention of consumer’s purchase behavior and shows the boundary conditions of predictive power of loyalty intention and past purchase on future purchase. Moreover, this is one of the very few studies that have focused on these relationships in Indian context.

The purpose of this paper is to establish what foresight is, to review past usages and definitions of foresight and to synthesize them into one generic definition, in order to make the concept measurable.

A discussion on how to classify variables in the social sciences serves as the starting‐point. Next, a review of past definitions and usages of the concept foresight is followed by further analysis and then synthesizing of the generic definition. The generic definition is finally compared and contrasted with the related concepts of forecasting, strategic analysis, and intuition.

Foresight is defined as behavior along three dimensions: degree of analyzing present contingencies and degree of moving the analysis of present contingencies across time; degree of analyzing a desired future state or states a degree ahead in time with regard to contingencies under control; and degree of analyzing courses of action a degree ahead in time to arrive at the desired future state.

The article makes foresight quantitatively measurable, which in turn makes it possible to empirically measure the existence of foresight among managers and to test the relationship between foresight and organizational performance.

Practical foresight tools and programs, etc. can now be assessed and compared by both practitioners and researchers.

In identifying three fundamental behavioral dimensions of foresight, the article conceives and advances foresight as a distinct concept that can be related to several research areas, both on individual (e.g. managerial) and organizational levels.