Search results

The purpose of this paper is to identify and quantify the key components of the overall cost of software development when warranty coverage is given by a developer. Also, the authors have studied the impact of imperfect debugging on the optimal release time, warranty policy and development cost which signifies that it is important for the developers to control the parameters that cause a sharp increase in cost.

An optimization problem is formulated to minimize software development cost by considering imperfect fault removal process, faults generation at a constant rate and an environmental factor to differentiate the operational phase from the testing phase. Another optimization problem under perfect debugging conditions, i.e. without error generation is constructed for comparison. These optimization models are solved in MATLAB, and their solutions provide insights to the degree of impact of imperfect debugging on the optimal policies with respect to software release time and warranty time.

A real-life fault data set of Radar System is used to study the impact of various cost factors via sensitivity analysis on release and warranty policy. If firms tend to provide warranty for a longer period of time, then they may have to bear losses due to increased debugging cost with more number of failures occurring during the warrantied time but if the warranty is not provided for sufficient time it may not act as sufficient hedge during field failures.

Every firm is fighting to remain in the competition and expand market share by offering the latest technology-based products, using innovative marketing strategies. Warranty is one such strategic tool to promote the product among masses and develop a sense of quality in the user’s mind. In this paper, the failures encountered during development and after software release are considered to model the failure process.

The software development team reviews the testing phase to assess if the reliability growth of software is as per plan and requirement and gives suggestions for improvement. The objective of this study is to determine the optimal review time such that there is enough time to make judgments about changes required before the scheduled release.

Testing utilizes majority of time and resources, assures reliability and plays a critical role in release and warranty decision-making reviews necessary. A very early review during testing may not give useful information for analyzing or improving project performance, and a very late review may delay product delivery and lead to opportunity loss for developers. Therefore, it is assumed that the optimal time for review is in the later stage of testing when the fault removal rate starts to decline. The expression for this time point is determined using the S-curve 2-D software reliability growth model (SRGM).

The methodology has been illustrated using the real-life fault datasets of Tandem computers and radar systems resulting in optimal review time of 14 weeks and 26 months, respectively, which is neither very early in testing nor very near to the scheduled release. The developer can make changes (more resources or postpone release) to expedite the process.

Most of the literature studies focus on determination of optimal testing or release time to achieve considerable reliability within the budget, but in this study, the authors determine the optimal review time during testing using SRGM to ensure the considerable reliability at release.

Nowadays, various hotels and third party websites allow guests to express their stay experience in the form of textual content and ratings termed as user-generated content (UGC). This study aims to explore the influence of UGC along with the financial aspect on the sales of the hotel. This will help them in making efficient business decisions and revenue generation by realizing the requirements of the guests. The proposed model provides an insight into the theoretical and practical significance of the concerned explanatory variables to the hoteliers.

This paper considers the number of rooms, six aspect ratings (room, cleanliness, location, service, value and sleep quality), review length and readability as the independent variables. Revenue per available room is taken as the dependent variable. Log-linear regression analysis is performed on a data set of 78 hotels situated in Delhi National Capital Region to validate the relationships. Moreover, the differential impact of hotel type on these exploratory variables is studied.

Research findings show that along with the financial aspect, the UGC components also play a key role in generating sales for the hotels. It was further observed that the two hotel categories, i.e. luxury and budget have different natures and also the characteristics of luxury hotels overshadow those of budget.

This study uses the textual content of the reviews along with the numerical ratings. This is a unique combination for studying sales of hotels according to the knowledge of authors, where earlier studies focused only on the financial aspects.

The challenges and factors of household adoption and the use of alternative energy sources have been a point of discussion among researchers. The purpose of this study is to apply a variant of the unified theory of adoption and use of technology (i.e. UTAUT 2) to explore the effect of various constructs that influence technology adoption on the consumers’ intention to adopt (and use) solar power generators (SPG) at the household level and the subsequent switching behavior.

Based on survey data collected from six cities in India (n = 1,246), factor analysis and structural equation modeling are applied for data analysis and testing the study hypotheses.

The results of the structural equation model found UTAUT constructs performance expectancy, effort expectancy, social influence and hedonic to positively affect behavioral intentions to adopt SPG. However, facilitating conditions and perceived value was not found to affect behavioral intentions to adopt SPG. Behavioral intentions to adopt SPG was found to positively influence the switching behavior.

The present study augments the domain of alternative energy usage behavior by applying the UTAUT 2 in the adoption of alternative energy sources (namely, solar) and subsequent switching behavior from traditional sources at the household level.

The findings from the present study will guide the marketers and policymakers on the consumer attitudinal and behavioral aspects of solar energy usage at the household level and subsequent switching behavior.

The present study is novel as it moves beyond household-level behavioral intention to use solar energy and includes the switching behavior to shift to solar power from traditional energy sources.

It is becoming easier for end-users to modify their information system, sometimes against the wishes of management or the original manufacturer. In the mobile device context, “modding”, “jailbreaking” or “rooting” allows a mobile phone user to select operating software and network providers other than those mandated by the original provider. Prior studies have theorised that modders and non-modders possess different perspectives on the relationship between them and their device provider. However, these differences have not been empirically demonstrated in prior work. This paper aims to test theoretical pathways to explain the behavioural relationship effects of security within the modding context.

This study models four relationship conceptualisations from prior research. The study tests this model using a survey of 464 mobile device users to compare the user attitudes of modders and non-modders.

Modder and non-modder relationships differ. Both groups value security, but in different ways: modder relationships are governed by satisfaction and commitment, while non-modder relationships are governed more by trust.

To the best of the authors’ knowledge, this is the first study to empirically demonstrate the relationship differences between IS modifiers and non-modifiers. Most published work has focused on IS that are unmodified. Incorporating device modification may improve behavioural understanding of end-users.

The emergence of widely available Generative Artificial Intelligence (GenAI) tools, such as ChatGPT, presents both opportunities and threats for higher education. This study aims to investigate the factors that influence students’ current use of GenAI and students’ perceptions of how GenAI can facilitate learning, as well as informs recommendations for institutional policies related to GenAI.

A mixed-method approach was used. A survey of undergraduate business students was followed by a case study that required students to use GenAI as part of a homework assignment and then reflect on their learning experience.

Students used GenAI more frequently when they perceived that it helped their learning outcomes and when it was perceived as a social norm. Conversely, the perception that GenAI was cheating reduced its usage. Male (vs female) students used GenAI more frequently. Students preferred institutional policies that allowed the use of GenAI but also set clear boundaries for its use. They reported that the assignment that required the use of GenAI enhanced their learning experience.

Results from the survey and case study imply that institutions should set policies establishing clear boundaries for the use of GenAI while encouraging and training faculty to incorporate GenAI into classroom assignments. Doing so can facilitate student learning and train students on an important technology that prepares them for the workforce.

This study provides insight into students’ usage of GenAI, explores factors that predict its usage, provides policy recommendations for educational institutions and offers a template for incorporating GenAI into classroom assignments.

This paper presents the effects of replacing fine aggregate (FA) with waste foundry sand (WFS) in natural aggregate and construction waste aggregate concrete specimens without and with superplasticizer (SP), silica fume (SF) and fiber (F) to solve the disposal problems of various wastes along with saving the environment. This study aims to investigate the effect of construction waste, WFS along with additives on the stress-strain behavior and development of compressive strength with age.

The various concrete specimen were prepared in mix proportion of 1: 2: 4 (cement (C): sand: coarse aggregate). The water-cement ratio of 0.5 (decreased by 10% for samples containing SP) to grading 1: 2: 4 under air-dry condition was adopted in the preparation of concrete specimens. The compressive strength of various concrete specimen were noticed for 3, 7 and 28 days by applying load through universal testing machine.

Upon adding construction and demolition waste aggregates, the compressive strength of concrete after 28 days was comparable to that of the control concrete specimen. An enhancement in the value of compressive strength is perceived when FA is replaced with WFS to the extent of 10%, 20% and 30%. If both construction and demolition waste aggregate and WFS replacing FA are used, the compressive strength increases. When FA is interchanged with WFS in natural aggregate or construction demolition waste aggregate concrete including usage of SF or F, the compressive strength improves significantly. Further, when construction and demolition waste aggregate and WFS replacing FA including SP are used, the compressive strength improves marginally compared to that of control specimen. The rate of strength development with age is observed to follow similar trend as in control concrete specimen. Therefore, construction and demolition waste and or WFS can be used effectively in concrete confirming an improvement in strength.

The utilization of these wastes in concrete will resolve the problem of their disposal and save the environment.

This study aims to conduct a bibliometric analysis to provide a comprehensive picture and identify future research directions to enrich the existing literature on behavioral biases.

The data set comprises 518 articles from the Web of Science database. Performance analysis is used to highlight the significant contributors (authors, institutions, countries and journals) and contributions (highly influential articles) in the field of behavioral biases. In addition, network analysis is used to delve into the conceptual and social structure of the research domain.

The current review has identified four major themes: “Influence of behavioral biases on investment decisions,” “Determinants of home bias,” “Impact of biases on stock market variables” and “Investors’ decision-making under uncertainty.” These themes reveal that a majority of studies have focused on equity markets, and research on other asset classes remains underexplored.

This study extracted data from a single database (Web of Science) to ensure standardization of results. Consequently, future research could broaden the scope of the bibliometric review by incorporating multiple databases.

The novelty of this research is to provide valuable guidance by evaluating the existing literature and advancing the knowledge base on the conceptual and social structure of behavioral biases.