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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.

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.

The present study aims to examine the scope and contribution of behavioural investigative advice (BIA) reports from the National Crime Agency (NCA).

The 77 BIA reports reviewed were written between 2016 and 2021. They were evaluated using Toulmin’s (1958) strategy for structuring pertinent arguments, current compliance with professional standards, the grounds and backing provided for the claims made and the potential utility of the recommendations provided.

Consistent with previous research, most of the reports involved murder and sexual offences. The BIA reports met professional standards with extremely high frequency. The 77 reports contained a total of 1,308 claims of which 99% were based on stated grounds. A warrant and/or backing was provided for 73% of the claims. Most of the claims in the BIA reports involved a behavioural evaluation of the crime scene and offender characteristics. The potential utility of the reports was judged to be 95% for informative behavioural crime scene analysis and 40% for potential new lines of enquiry.

The reports should serve as a model for the work of behavioural investigative advisers internationally.

To the best of the authors’ knowledge, this is the first study to systematically evaluate BIA reports commissioned by the NCA; it adds to previous similar studies by evaluating the largest number of BIA reports ever reviewed, and uniquely provides judgement of overall utility.

Images and caption descriptions serve as important visual stimuli that influence consumer preferences; therefore, the current study focuses on property images and captions illustrated on the home pages of accommodation-sharing platforms. Specifically, this study investigates the relative importance of hue, brightness and saturation of a property image and caption description styles on potential consumers’ preferences.

A mixed-method approach was used, and a total of 293 valid responses were collected through a discrete choice experiment approach. Interviews were conducted for additional analyses to explore the detailed explanations.

The utility model demonstrated that the image’s saturation was the most critical attribute perceived by the respondents, followed by caption description style, hue and brightness.

This is one of the first studies to investigate the display of attributes on a digital accommodation platform by exploring potential customers’ stated preferences. This study focuses explicitly on images and captions illustrated on the home page of an accommodation booking platform. Detailed image investigation is also a new research area in sharing economy-related research.

This study is centered on the identification of the most appropriate Technology Adoption (TA) model for investigating the adoption of Industry 4.0 technologies within pharmaceutical and related enterprises. The aim is to facilitate a smooth transition to advanced technologies while concurrently achieving environmental sustainability.

Selection of a suitable TA theory is carried out using a hybrid multi-criteria decision-making (MCDM) approach incorporating PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA) and Fuzzy Measurement of alternatives and ranking according to Compromise solution (F-MARCOS) methods. A group of three experts is formulated for the ranking of criteria and alternatives based on those criteria.

The results indicate that out of all six TA models considered unified theory of acceptance and use of technology (UTAUT) model gets the highest utility function value, followed by the technical adoption model (TAM). Further, sensitivity analysis is conducted to confirm the validity of the MCDM model employed.

Challenging times like COVID-19 pointed out the importance of technology in the pharmaceutical and healthcare sectors. TA studies in this area can help in the identification of critical factors that can assist pharmaceutical firms in their efforts to embrace emerging technologies, enhance their outputs and increase their efficiency.

The novelty of this research lies in the fact that the utilization of a TA theory prior to its implementation has not been witnessed in existing scholarly literature. The utilization of a TA theory, specifically within the pharmaceutical industry, can assist enterprises in directing their attention toward pertinent factors when contemplating the implementation of emerging technologies and achieving sustainable development.

Infection and cross-contamination have been massive concerns in the medical field. This study aims to investigate consumers’ awareness and their choices of endoscopes, which may deter them from the cross-contamination problem.

A discrete choice experiment survey was administered to 166 respondents in Penang, Malaysia. Participants were asked to make hypothetical choices and estimate their preference for endoscopes. The multinomial logit model was used to estimate the assumptions based on the stated preference data collected.

Only two-fifths of respondents are aware of their rights regarding endoscope selection. The findings are consistent with utility theory, where choices are made to maximise personal satisfaction. If given the choice, consumers preferred the single-use endoscope over the reusable or the doctor’s preferred endoscope. Price, insurance coverage and personal income are significant determinants of the consumer’s choice of endoscopes.

This study only investigates subjects living in Penang. Other possible important attributes to endoscope choices, such as environmental and device availability may be considered in future study.

The findings may create awareness among consumers about their rights when choosing medical devices. It may also improve health-care institutions’ (users’) and device manufacturers’ (industry players’) understanding of consumer needs and demands from socioeconomic perspectives.

The research offers insights into consumer rights and awareness of health-care services. Ultimately leading to better policy to protect consumers’ rights and safety.

This study contributes to the rare literature on consumer rights toward medical devices, in particular, the consumer’s awareness of the choice of endoscopes.

The current and modern electrical distribution networks, named smart grids (SGs), use advanced technologies to accomplish all the technical and nontechnical challenges naturally demanded by energy applications. Energy metering collecting is one of these challenges ranging from the most basic (i.e., visual assessment) to the expensive advanced metering infrastructure (AMI) using intelligent meters networks. The AMIs’ data acquisition and system monitoring environment require enhancing some routine tasks. This paper aims to propose a methodology that uses a distributed and sustainable approach to manage wide-range metering networks, focused on using current public or private telecommunication infrastructure, optimizing the implementation and operation, increasing reliability and decreasing costs.

Inspired by blockchain technology, a collaborative metering system architecture is conceived, managing massive data sets collected from the grid. The use of cryptography handles data integrity and security issues.

A robust proof-of-concept simulation results are presented concerning the resilience and performance of the proposed distributed remote metering system.

The methodology proposed in this work is an innovative AMI solution related to SGs. Regardless of the implementation, operation and maintenance of AMIs, the proposed solution is unique, using legacy and new technologies together in a reliable way.

The aim of this paper is to examine the existing literature circa 2010–2023 of introductory wine education involving sensory experience components in an objective, transparent and replicable manner. Sensory experience education normally involves the usage of the five senses (smell, taste, sight, feel and hearing) as means to demonstrate, scaffold and illuminate introductory-level wine curricula. This study identifies the methodologies used in existing in educational wine sensory experience literature, identifies the pedagogical utilities of current wine research and explores findings useful for wine educators.

This paper uses the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) for literature review reporting.

From the existing body of literature involving wine sensory experience in education (N = 20), five pedagogical utilities emerged from the dataset: wine sensory experience training (n = 7), wine sensory analysis techniques (n = 5), teaching environment (n = 5), wine and food pairing (n = 2) and psychological context (n = 1). Furthermore, experimental design is the preferred method (n = 14) of research related to wine sensory experience in education.

This study provides utility for wine educators at the college and university level and may provide perspective and tools for firms seeking consumer engagement through wine education.

To the researchers' knowledge, there are no literature reviews that explore wine sensory experience in education. Thus, the primary contributions of this study are threefold: identification of current gaps in wine education research, identification of future research questions and avenues of study, and resources for curriculum improvement of introductory wine courses.

Cotton fibre lots are graded and selected for yarn spinning based on their quality value which is a function of certain fibre properties. Cotton grading and selection has created a domain of emerging interest among the researchers. Several researchers have addressed the said issue using a few exponents of multi-criteria decision-making (MCDM) technique. The purpose of this study is to demonstrate a cotton selection problem using a recently developed measurement of alternatives and ranking according to compromise solution (MARCOS) method which can handle almost any decision problem involving a finite number of alternatives and multiple conflicting decision criteria.

The MARCOS method of the MCDM technique was deployed in this study to rank 17 cotton fibre lots based on their quality values. Six apposite fibre properties, namely, fibre bundle strength, elongation, fineness, upper half mean length, uniformity index and short fibre content are considered as the six decision criteria assigning weights previously determined by an earlier researcher using analytic hierarchy process.

Among the 17 alternatives, C9 secured rank 1 (the best lot) with the highest utility function (0.704) and C7 occupied rank 17 (the worst lot) with the lowest utility function (0.596). Ranking given by MARCOS method showed high degree of congruence with the earlier approaches, as evidenced by high rank correlation coefficients (Rs > 0.814). During sensitivity analyses, no occurrence of rank reversal is observed. The correlations between the quality value-based ranking and the yarn tenacity-based rankings are better than many of the traditional methods. The results can be improved further by adopting other efficient method of weighting the criteria.

The properties of raw cotton have significant impact on the quality of final yarn. Compared to the traditional methods, MCDM is reported as the most viable solution in which fibre parameters are given their due importance while formulating a single index known as quality value. The present study demonstrates the application of a recently developed exponent of MCDM in the name of MARCOS for the first time to address a cotton fibre selection problem for textile spinning mills. The same approach can also be extended to solve other decision problems of the textile industry, in general.

Novelty of the present study lies in the fact that the MARCOS is a very recently developed MCDM method, and this is a maiden application of the MARCOS method in the domain of textile, in general, and cotton industry, in particular. The approach is very simple, highly effective and quite flexible in terms of number of alternatives and decision criteria, although highly robust and stable.