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As public–private partnerships (PPPs) have become preferred and veritable approach to deliver affordable housing, the seemingly lack of understanding of the significant factors that impact on success has become a notable setback. This study aims to delineate significant factors that can support decisions in affordable PPP public housing delivery.

Largely, a questionnaire survey was adopted to elicit insights from practitioners, policymakers and experts to develop an evaluative decision support model using an analytical hierarchy process and multi-attribute utility technique approach. Further, an expert illustration was conducted to evaluate and validate the results on the housing typologies.

The results revealed that energy efficiency and low-cost green building materials scored the highest weighting of all the criteria. Furthermore, multi-storey self-contained flats were found to be the most preferred housing typology and were significantly influenced by these factors. From the model evaluation, the scores on the factors of sustainability, affordability, cultural values and accountability were consistent across all typologies of housing whereas that of benchmarking, governance and transparency were varied.

The decision support factors captured varied dimensions of key factors that impact on affordable PPP housing that have not been considered in an integrated manner. These findings offer objective and systematic support to decision-making in affordable PPP housing delivery.

Over the last three decades, construction projects have increasingly been delivered through alternative delivery methods. As a result, many owners have a range of delivery methods to choose from and aim to use the right one for each of their projects. Researchers have developed several tools and decision-support processes to facilitate this selection procedure. The purpose of this study is to review and discuss differences and common themes across selection tools developed by academic researchers and project owners.

The study reviews prominent selection processes and tools used for infrastructure projects by conducting an in-depth literature review and using the content analysis method to elicit findings on the methodologies and criteria presented in the literature.

This study presents three principal findings. First, findings show three common themes emerge within the selection criteria—characteristics, goals and risks. Second, while academic studies most commonly suggest employing multi-attribute analysis, this study reveals that, in practice, selection tools most frequently employ a staged or gated evaluation based on the type of criteria and their importance to the decision. Finally, this review further highlights the importance of institutional context in decision-making.

This work contributes to the body of knowledge by providing guidance to practitioners and opening new directions for researchers around the way selection criteria are categorized in the relevant literature and the institutional context considerations when structuring or evaluating a selection process or tool.

This research paper explores customer experience (CX) among low-literate customers in organized retail environments. It integrates theories from customer literacy, CX and patronage literature to understand CX comprehensively.

The study gathered data from 470 respondents using mall intercept and snowball sampling. Data analysis employed partial least squares (PLS) modeling.

The results indicate that all the dimensions do not have the same effect on CX. Answering calls for future research, the results establish CX's nomological validity by showing its positive influence on retail reputation, retail quality and satisfaction. However, it does not directly affect patronage but has an indirect influence through retail quality and satisfaction. Also, the authors conclude that retail quality and satisfaction are consequences of CX and not previously conceptualized proxies for it.

Conducting primary research with low-literate customers (LLCs) has its own set of limitations that give rise to further research directions. While acknowledging limitations, the study suggests avenues for future research by surveying LLCs with an objective questionnaire, contributing to limited empirical research in this segment.

The findings highlight the multidimensional nature of CX. In summary, this research paper provides insights into CX dimensions and outcomes for LLCs in organized retail. It contributes to marketing literature, assisting retailers in improving CX and driving patronage across customer segments.

The paper contributes to marketing literature by studying LLCs, testing a comprehensive CX model, confirming antecedents in retail patronage and exploring reciprocal relationships in retailing.

Building a smart city is a necessary path to achieve sustainable urban development. Smart city public–private partnership (PPP) project is a necessary measure to build a smart city. Since there are many participants in smart city PPP projects, there are problems such as uneven distribution of risks; therefore, in order to ensure the normal construction and operation of the project, the reasonable sharing of risks among the participants becomes an urgent problem to be solved. In order to make each participant clearly understand the risk sharing of smart city PPP projects, this paper aims to establish a scientific and practical risk sharing model.

This paper uses the literature review method and the Delphi method to construct a risk index system for smart city PPP projects and then calculates the objective and subjective weights of each risk index through the Entropy Weight (EW) and G1 methods, respectively, and uses the combined assignment method to find the comprehensive weights. Considering the nature of the risk sharing problem, this paper constructs a risk sharing model for smart city PPP projects by initially sharing the risks of smart city PPP projects through Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to determine the independently borne risks and the jointly borne risks and then determines the sharing ratio of the jointly borne risks based on utility theory.

Finally, this paper verifies the applicability and feasibility of the risk-sharing model through empirical analysis, using the smart city of Suzhou Industrial Park as a research case. It is hoped that this study can provide a useful reference for the risk sharing of PPP projects in smart cities.

In this paper, the authors calculate the portfolio assignment by EW-G1 and construct a risk-sharing model by TOPSIS-Utility Theory (UT), which is applied for the first time in the study of risk sharing in smart cities.

This study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their positioning in terms of SC performance.

A case study is used to demonstrate the set-up of the observatory. Twelve experts on automatic equipment for the wrapping and packaging industry were asked to select a set of performance criteria taken from the literature and evaluate their importance for the chosen industry using multi-criteria decision-making (MCDM) techniques. To handle the high number of criteria without requiring a high amount of time-consuming effort from decision-makers (DMs), five subjective, parsimonious methods for criteria weighting are applied and compared.

A benchmarking methodology is presented and discussed, aimed at DMs in the considered industry. Ten companies were ranked with regard to SC performance. The ranking solution of the companies was on average robust since the general structure of the ranking was very similar for all five weighting methodologies, though simplified-analytic hierarchy process (AHP) was the method with the greatest ability to discriminate between the criteria of importance and was considered faster to carry out and more quickly understood by the decision-makers.

Developing an SC observatory usually requires managing a large number of alternatives and criteria. The developed methodology uses parsimonious weighting methods, providing DMs with an easy-to-use and time-saving tool. A future research step will be to complete the methodology by defining the minimum variation required for one or more criteria to reach a specific position in the ranking through the implementation of a post-fact analysis.

This study aims to examine the role of experiential familiarity in determining the competitiveness of hotel chains. It does so by comparing the attribute-performance perceptions of guests who had and had not previously stayed at a property belonging to a specific hotel chain. It also examines how far such perceptions shape word-of-mouth and future purchase intentions.

Data were collected from 1,016 Finnish leisure tourists in 2021 using an online questionnaire, providing a representative sample of Finnish domestic leisure tourists.

The results indicate that the competitiveness of different hotel chains depends on a small number of key attributes. Differentiation between hotel chains can be seen from the results. Previous guests rate hotel chain attributes more highly than non-previous guests. Behavioral intentions do not differ between previous and non-previous guests, but how many times a person has stayed in the hotel chain significantly influences behavioral intentions. The results provide strategic levers that hotel chains can use to enhance their competitiveness.

Hotels should invest in attributes that have the biggest positive impact on customer behavior. These will be different for different hotel chains. By understanding these differences, it is possible to communicate relevant attributes to customers through marketing and develop hotel features that will drive revisit intention and word-of-mouth marketing.

This study found that while certain hotel attributes had a significant shaping effect on guests’ performance ratings, there were no decisive differences between those with or without experiential familiarity with the hotel chain.

Quality assessment of textile products is of prime concern to intimately meet consumer demands. The dilemma faced by textile producers is to figure out the stability among quality criteria and efficiently deal with target specifications. Hence, the basic devotion is to attain the optimum value product which entirely satisfies the views and perceptions of consumers. Selection of best fabric among several alternatives in the presence of contradictory measures is a disputing problem in multicriteria decision-making.

In the current study, the analytic hierarchy process (AHP) and preference ranking organization method for enrichment evaluation (PROMETHEE) are proficiently used to solve the problem in selection of branded woven shawls. AHP method verifies comparative weights of the criteria selection, while the ranking of fabric alternatives grounded on specific net-outranking flows is executed through PROMETHEE II method.

The collective AHP and PROMETHEE approaches are applied for the useful accomplishment of grading of branded shawls based on multicriteria weights, used for effective selection of fabric materials in the textile market.

In the apparel industry, fabric and garment manufacturers often rely on hit-and-trial methods, leading to significant wastage of valuable resources and time, in achieving the desirable fabric qualities. The implementation of the findings can assist apparel manufacturers in streamlining their fabric selection processes based on multiple criteria. By adopting this method, industry players can make informed decisions, ensuring a balance between quality standards and consumer expectations, thereby enhancing both product value and market competitiveness.

The methods of Visual PROMETHEE and AHP are assimilated to offer a complete method for the selection and grading of fabrics with reference to multiple selection criteria.

The main objective of this study was to establish a model of competitiveness factors to measure the value of construction companies adequately.

A theoretical model of four main factors was developed, and they include human capital, ethical values, process innovation and financing. Information was collected from 18 construction companies in the city of Metropolitan Lima, collecting information on each of these factors. Through an analysis of the principal components, the weighting of each factor about the competitiveness of a construction company was determined.

The cost of person-hours, the cost of equipment to execute work, and the cost of materials used are the strongest indicators to measure the competitiveness of a construction company. On the other hand, the number of employees holding university degrees and the number of master builders holding technical degrees in the human capital factor also have a moderate weight in determining the competitiveness value of a company. The indicator of work delivered within the deadline also moderately affects competitiveness. Finally, the monthly debt payment indicator has a very small effect on the company’s competitiveness.

In conclusion, this study provides evidence of a competitiveness model with highly related factors on human capital, process innovation and ethical values as the most important in measuring competitiveness.

El objetivo principal de la investigación fue establecer un modelo de factores de competitividad para medir adecuadamente el valor de las empresas constructoras.

Se desarrolló un modelo teórico de cuatro factores principales, que incluyen el capital humano, los valores éticos, la innovación de procesos y el financiamiento. Se recolectó información de 18 empresas constructoras de la ciudad de Lima Metropolitana, recolectando información de cada uno de estos factores. A través de un análisis de componentes principales se determinó la ponderación de cada uno de ellos sobre la competitividad de una empresa constructora.

El costo de horas hombre, el costo de los equipos para ejecutar obras y el costo de material utilizado son los indicadores más fuertes para medir la competitividad de una empresa constructora. Por otro lado, la cantidad de empleados con títulos universitarios y la cantidad de maestros de obra con título técnico del factor de capital humano también tienen un peso moderado en la determinación del valor de competitividad de una empresa. El indicador de obras entregadas dentro de plazo también tiene un efecto moderado sobre la competitividad. Finalmente, el indicador de pago mensual de la deuda tiene un efecto muy pequeño sobre la competitividad de la empresa.

En conclusión, el estudio proporciona evidencia de un modelo de competitividad con factores altamente relacionados sobre el capital humano, la innovación de procesos y los valores éticos como los más importantes a la hora de medir la competitividad.

Quality Assurance and Improvement Program (QAIP) is defined as “an ongoing and periodic assessment of the entire spectrum of audit and consulting work performed by the internal audit (IA) activity”. QAIP is an important component of internal auditors’ commitment to improve internal audit (IA) quality. The pressure towards improvement is urgent for central banks, in light of the vulnerabilities of their IA functions identified by the International Monetary Fund. The authors analyse the professional standards and the literature on IA and QAIP, aiming to propose general considerations to enhance IA quality and to develop and maintain a QAIP, with reference to central banks, also shedding light on the synergies among IA, QAIP and total quality management (TQM).

This paper reviews the most relevant professional standards in light of the professional and academic literature regarding IA quality, QAIP and their relationship with TQM. The analysis of these sources represents an important step to identify general measures to improve IA quality and develop effective QAIP in central banks.

This analysis shows that it is important to understand the rationale behind the development of an IA function and its theoretical and practical foundation, especially for complex organisations such as central banks. In addition, the authors show that QAIP represents an important tool to exploit the synergies between TQM and IA. These synergies could result in higher levels of quality for the IA function and more effective implementation of TQM within the whole organisation. Lastly, the authors provide practical suggestions to support the implementation of an effective QAIP in central banks and to spread TQM philosophy within the organisation.

The authors contribute to the scant literature on IA quality and QAIP by focusing on central banks and shedding light on the relationship with TQM. Regardless of their importance, these topics have been largely neglected by the extant literature.

This study evaluated the enhancement of information sharing practices with third party logistics service providers (3PLs) in a supply chain solutions company that provides transport and warehousing software in Johannesburg, South Africa.

A mixed methods case study was conducted to investigate the problem. Both strands of quantitative and qualitative data were given equal priority. Three rounds of primary data were sequentially collected, analysed and triangulated. An online questionnaire was distributed to a sampling frame of seventeen companies which were randomly selected from the population. Three company executives were purposively sampled to participate in a focus group interview. Data from an open-ended questionnaire were used to explain and validate the findings from clients and executives who participated in the two preceding rounds of data collection.

It was found that information sharing improves the collaboration of channel members, increases competitive advantage and ultimately leads to better customer service. The improvement of relationships and continuous technological upgrades are recommended for improving visibility of information and effectiveness in the management of supply chains.

This study is limited by the characteristics of the case study methodology. Case study research suffers from restricted generalisability, problems with cross-checking and the risk of bias and subjectivity. This implies that the results of this case study may not be generalised to the overall population. The selection of a mixed methods design was intended to curb the limitations that are inherent to this study.

This study was limited to a few respondents and participants, which raises concerns about both the statistical power and the generalisability of the results. However, the results provide useful insights into some of the information sharing practices in the industry.

The value of the study contributes to the supply chain's dependence on 3PLs for value creation and the reliance on technology to share information amongst channel members. This study highlights a need for organisations to build collaborative relationships with 3PLs and continuously update technological infrastructure in order to meet supply chain network goals.