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Delays in utility shifting during road construction have broad ramifications. These delays not only lengthen the project's timeline but also raise expenses and cause problems with resource allocation. Thus, this study investigates the influence of delay in utility shifting for extension of time claims in road construction projects (RCPs) in Sri Lanka.

The study used a quantitative approach with three rounds of Delphi surveys to gather empirical data. Further, the probability impact assessment was used to carefully analyse the data and appraise the information gathered.

The findings initially revealed 33 causes of delays in utility shifting for extension of time claims in RCPs in Sri Lanka. Ultimately, 11 severe causes were identified based on their high probability and impact, concluding with 45 strategies that were assigned to overcoming those most severe causes of delay.

This study will contribute to the industry and theory by providing solutions to handle utility-shifting delays with the linkage of preventing time extension claims for RCPs in Sri Lanka. Further, there is a dearth of literature in the research area, both locally and globally. Thus, the findings of this research will provide a benchmark for further detailed studies in other countries as well.

With the development of digitalization and interconnection, there is a growing need for enterprise customers to ensure the compatibility of the third-party components they are using in the manufacturing process, thus raising the integration requirements for the Industrial Internet platform and its third-party developers. Therefore, our study investigates the optimal integration decision of the Industrial Internet platform while considering its access price, the integration cost, and the net utility derived by enterprise customers from the third-party components.

We model a two-sided Industrial Internet platform that connects customers on the demand side to the developers on the supply side. We then explore the integration decision of the Industrial Internet platform and its important factors by solving the optimal profit function.

First, despite the high integration cost of third-party developers, the platform still chooses to integrate when enterprise customers derive high utility from the third-party components. Second, due to the compatibility effect, charging the enterprise customers a higher price may reduce the platform profits when these customers derive low utility from the third-party components. Third, the platform profits will increase along with the integration cost of third-party developers when it is low in the case where enterprise customers derive low utility from third-party components.

Our findings offer insightful takeaways for the Industrial Internet platform when making integration decisions.

This study aims to investigate the impact of pollution control bonds (PCBs) on overinvestment within utility firms.

This empirical study analyzes a data set comprising 215 US energy firms observed from 2011 to 2021, using the ordinary least square regression with standard errors adjusted for firm-level clustering.

The study reveals a negative relationship between PCBs and overinvestment, indicating that PCBs are an effective tool in curbing excessive investment. Additionally, it demonstrates that chief executive officer (CEO) overconfidence diminishes the influence of PCBs on overinvestment. These findings remain robust across various metrics for measuring overinvestment and CEO overconfidence, as well as when alternative estimation methods are used. These results align with insights derived from agency theory and upper echelon theories.

Regulators are encouraged to actively promote the use of PCBs as a financing tool for environmentally focused initiatives. To achieve this, regulatory bodies should enhance their presence within the utility sector, particularly in regions grappling with higher pollution levels. This requires the implementation of strategic policies and regulatory frameworks aimed at mitigating excessive investments. Simultaneously, policymakers should take proactive measures to introduce financial instruments designed to optimize investment efficiency, thus facilitating eco-friendly projects.

To the best of the authors’ knowledge, this paper holds the distinction of being the first to examine the impact of a specific type of green bond, namely, PCBs, on overinvestment. Furthermore, it contributes to the literature on personality traits, particularly within the context of the upper echelon theory, by investigating the moderating influence of CEO overconfidence.

This study was carried out to analyze the importance of consumer preference data in forecasting demand in apparel retailing.

To collect preference data, 729 hypothetical stock keeping units (SKU) were derived using a full factorial design, from a combination of six attributes and three levels each. From the hypothetical SKU's, 63 practical SKU's were selected for further analysis. Two hundred two responses were collected from a store intercept survey. Respondents' utility scores for all 63 SKUs were calculated using conjoint analysis. In estimating aggregate demand, to allow for consumer substitution and to make the SKU available when a consumer wishes to buy more than one item in the same SKU, top three highly preferred SKU's utility scores of each individual were selected and classified using a decision tree and was aggregated. A choice rule was modeled to include substitution; by applying this choice rule, aggregate demand was estimated.

The respondents' utility scores were calculated. The value of Kendall's tau is 0.88, the value of Pearson's R is 0.98 and internal predictive validity using Kendall's tau is 1.00, and this shows the high quality of data obtained. The proposed model was used to estimate the demand for 63 SKUs. The demand was estimated at 6.04 per cent for the SKU cotton, regular style, half sleeve, medium priced, private label. The proposed model for estimating demand using consumer preference data gave better estimates close to actual sales than expert opinion data. The Spearman's rank correlation between actual sales and consumer preference data is 0.338 and is significant at 5 per cent level. The Spearman's rank correlation between actual sales and expert opinion is −0.059, and there is no significant relation between expert opinion data and actual sales. Thus, consumer preference model proves to be better in estimating demand than expert opinion data.

There has been a considerable amount of work done in choice-based models. There is a lot of scope in working in deterministic models.

The proposed consumer preference-based demand estimation model can be beneficial to the apparel retailers in increasing their profit by reducing stock-out and overstocking situations. Though conjoint analysis is used in demand estimation in other industries, it is not used in apparel for demand estimations and can be greater use in its simplest form.

This research is the first one to model consumer preferences-based data to estimate demand in apparel. This research was practically tested in an apparel retail store. It is original.

The study aims to address a critical gap in existing healthcare payment schemes and care service pricing by recognizing the influential role of patients' decisions on self-management efforts. These decisions not only impact health outcomes but also shape the demand for care, subsequently influencing care costs. Despite the significance of this interplay, current payment schemes often overlook these dynamics. The research focuses on investigating the implications of a novel behavior-based payment scheme, designed to align incentives and establish a direct connection between patients' decisions and care costs. The primary objective is to comprehensively understand whether and how this innovative payment scheme structure influences key stakeholders, including patients, care providers, insurers and overall social welfare.

In this paper, we propose a game-theoretical model to incorporate the performance of self-management with the demand for healthcare service, compare the patient's effort decision for self-management and provider's price decision for healthcare service under a behavior-based scheme with that under two implemented widely payment schemes, that is, co-payment scheme and co-insurance scheme.

Our findings confirm that the behavior-based scheme incentives patient self-management more than current schemes while reducing their possibility of seeking healthcare service, which indirectly induces the provider to lower the price of the service. The stakeholders' utility under various payment schemes is sensitive to the cost of treatment and the perceived health utility of patients. Especially, patient health awareness is not always benefited provider profit, as it motivates patient self-management while diminishing the demand for care.

We provide a novel framework for characterizing behavior-based payment schemes. Our results confirm the need for modification of the current payment scheme to incentivize patient self-management.

This study aims to establish the effect of environmental, social and governance (ESG) practices on Australian energy and utility investment performance.

Conventional and ESG-rated portfolios are constructed using monthly returns and ESG scores of S&P/ASX 300 listed energy and utility firms from 2014 to 2022. Portfolio performance is estimated using a four-factor regression model, controlling for any economic shocks associated with the COVID-19 pandemic.

The findings show that the lower the ESG score associated with the overall ESG and environmental portfolios, the greater the performance compared to the market (but not the conventional and other ESG portfolios). High ESG scores do not appear to influence the performance of the energy and utility portfolios, which contrasts expectations that the uptake of ESG should deliver superior risk-return outcomes for investors. The findings also indicate that a contrarian investment approach may be a reasonable performance indicator for high-rated ESG portfolios. ESG practices did not impact portfolio performance during the COVID-19 pandemic.

This research has contributed to the literature by offering ESG investment insights for policymakers, regulators, fund managers and investors. Consistent with the agency perspective on ESG practices and efficient market hypothesis, the evidence implies that, regardless of ESG scores (either high or low), investors should consider investing passively in diversified energy and utility portfolios or low-cost index fund equivalents.

The purpose of this study is to examine the buyers’ preferences influencing the purchase of privately developed affordable housing in Kolkata and to determine whether unsold houses result from misalignment with these preferences.

The literature review and user-opinion survey identified 119 independent variables that indicate buyers’ preferences. A questionnaire survey of 383 households in affordable housing units from 32 housing complexes in Kolkata recorded buyers’ preferences and satisfaction against the independent variables grouped under five levels of characteristics. The product weights of variables derived from the rank sum method and percentage satisfaction give the Utility Score. Multivariate regression and univariate linear regressions were conducted to determine the significance of each Level of characteristics and each variable, identifying the significant variables that would affect the sale of affordable houses.

The multivariate regression analysis has indicated that 68.56% of the variation in the percentage of unsold houses was explained by the five utility scores, which affirms that misalignment with buyers’ preferences significantly affects the sale of privately developed affordable houses. Furthermore, building and neighbourhood-level utility show the highest significance as predictors, while city-level and miscellaneous utility have moderate significance, but housing complex-level utility lacks statistical significance.

This study addresses a research gap in privately developed affordable housing in Kolkata, enhancing understanding of buyer preferences in this segment.

This paper aims to analyze the synergistic influence of performance appraisal (PA) practices and performance-driven culture (PDC) on the effectiveness of the performance management (PM) system, which is measured by employees' reactions, namely satisfaction and perceived utility. It also analyzes the type of relationship between PA practices and PA satisfaction, specifically whether it is additive or modeled as a latent factor.

This is a cross-sectional study. Data were collected from 513 managers and employees working in 135 public and private organizations. The research model and hypotheses were tested using structured equation modeling.

The results support the positive impact of a set of four PA best practices on PA satisfaction. It shows that PDC is an enabler for the effective deployment of PA practices. It also demonstrates that the perceived utility of the PM system plays a role as a mediator in the relationship between PA practices and PA satisfaction.

Data were collected using a questionnaire at a single point in time, and thus, cause-and-effect inferences were not possible.

The results provide guidance to organizations that are interested in designing and implementing PM systems and PA practices that contribute toward enhancing employees' managing performance experiences.

This study advances our understanding of the mechanisms by which organizational culture and PA practices influence the effectiveness of the PM system. It suggests that organizations, to benefit the most from a set of PA best practices, need to have a PDC.

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.

Omnichannel has become increasingly important with the development of e-commerce. In omnichannel, merchants expect customers to get the products and services at anytime, anywhere and in any way, and the same is true for customers. This drives multihoming in online platforms for both merchants and customers. Thus, once both customers and merchants are multihomed, what price and subsidy decisions should be made between platforms to compete to obtain optimal profits? The main purpose of this paper is to solve these problems and provide decision-making for two-sided platforms in omnichannel.

This study builds a dual Hotelling model to capture the utility and network effects of customers and merchants on two-sided platforms. This study introduces the exposure effect and convenience effect of multihomed customers and merchants in the model and analyzes the impact of these effects in the market with multihoming on one side. Then, this study extends the model to the market with multihoming on both sides and makes the pricing decision for two-sided platform when considering the exposure effect and convenience effect through an equilibrium solution. Finally, this study also uses numerical analysis to simulate the decision and profit of the platform.

This paper finds that the convenience effect will only increase social welfare when customers are single-homed and merchants are multihomed. In addition, when both users are multihomed, the platform will subsidize to attract merchants and customers if the convenience effect and exposure effect are relatively high. This study also finds that network effects come not only from the same platform but also from another platform in the case with multihoming on both sides. And network effects in the heterogeneous platform will be reduced by the convenience effect and exposure effect.

According to the behavioral characteristics of merchants and customers in omnichannel, this paper first adopts the dual Hotelling model to study the pricing of two-sided platforms with multihoming on both sides. This paper shows that network effects originate not only from the same platform but also from another platform and that the exposure effect and the convenience effect can exist as cross-platform network effects, which provides a new explanation for network effects in markets with multihoming on both sides. This research extends the theory of network effects and plays an important role in the development of two-sided platforms in omnichannel.