This thesis aims to review and analyze the scheduling problem in general and Job Shop Scheduling Problem (JSSP) in particular and the solution techniques applied to these problems. The JSSP is the most general and popular hard combinational optimization problem in manufacturing systems. For the past sixty years, an enormous amount of research has been carried out to solve these problems. The literature review showed the inherent shortcomings of solutions to scheduling problems. This has directed researchers to develop hybrid approaches, as no single technique for scheduling has yet been successful in providing optimal solutions to these difficult problems, with much potential for improvements in the existing techniques. The hybrid approach complements and compensates for the limitations of each individual solution technique for better performance and improves results in solving both static and dynamic production scheduling environments. Over the past years, hybrid approaches have generally outperformed simple Genetic Algorithms (GAs). Therefore, two novel priority heuristic rules are developed: Index Based Heuristic and Hybrid Heuristic. These rules are applied to benchmark JSSP and compared with popular traditional rules. The results show that these new heuristic rules have outperformed the traditional heuristic rules over a wide range of benchmark JSSPs. Furthermore, a hybrid GA is developed as an alternate scheduling approach. The hybrid GA uses the novel heuristic rules in its key steps. The hybrid GA is applied to benchmark JSSPs. The hybrid GA is also tested on benchmark flow shop scheduling problems and industrial case studies. The hybrid GA successfully found solutions to JSSPs and is not problem dependent. The hybrid GA performance across the case studies has proved that the developed scheduling model can be applied to any real-world scheduling problem for achieving optimal or near-optimal solutions. This shows the effectiveness of the hybrid GA in real-world scheduling problems. In conclusion, all the research objectives are achieved. Finaly, the future work for the developed heuristic rules and the hybrid GA are discussed and recommendations are made on the basis of the results. / Board of Trustees, Endowment Fund Project, KPK University of Engineering and Technology (UET), Peshawar and Higher Education Commission (HEC), Pakistan

This study explores how shopping value in one-stop stores, especially hypermarkets, can be improved by new services. It identifies additional service offerings that go beyond the traditional product-based approach. Given the dearth of literature on new services in grocery retailing, this study relies on Mehrabian and Russel's (1974) stimulus-organism-response (S-O-R) model as a basic framework. Using an explorative mixed-methods approach, the study begins with a qualitative phase in which semi-structured interviews are conducted to uncover consumers' everyday problems. These findings serve as the basis for designing innovative services. In the subsequent quantitative phase, the study tests the theoretical framework by introducing participants to three different services in an experimental study. Based on the manipulation of the cognitive fit of services, various relationships between variables such as retailer confusion, perceived convenience, shopping value, retailer image, and willingness to use were examined. Results highlight the central role of cognitive fit, perceived convenience, and retailer confusion as key factors in shopping value, emphasizing its significance in shaping the retail landscape. This research not only identifies novel service opportunities for hypermarkets but also demonstrates the efficacy of a mixed-methods approach in addressing the evolving needs of consumers and the retail sector. The study provides also valuable insights for retailers seeking to differentiate themselves and enhance the shopping value.

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In this article, we analyse the factors influencing homeowners' plans to renovate their houses in the near future. We also examine their interest in the idea of a one-stop shop where a single actor provides services and all necessary information required for energy efficiency renovations. Our analysis is based on the content of an online survey questionnaire of 12194 homeowners in Sweden. Approximately 83% of the respondents intend to renovate in the near future, with around 55% opting for energy-efficient renovation of their dwelling. Environmental concerns, past energy-saving measures taken by the respondents, and education positively influenced their renovation plans. While 28% of respondents expressed their interest in a one-stop shop, work guarantee, environmental concerns and renovation plans were the main elements affecting interest in the one-stop shop.

This dissertation is a compilation of three essays that analyze price dispersion in an online retail marketplace. Price dispersion is a measure of the variation in prices that sellers charge for products. Online price dispersion has been thoroughly analyzed in the past decade as it has numerous implications for firm pricing strategy as well as consumer welfare. Chapter 1 of this dissertation offers a literature review of price dispersion research, and discusses key explanations as to why this phenomenon exists on the web. Also, a literature review of shop-bots is presented as they are similar to online marketplaces and form the basis of the three studies. Chapter 2 is the first study, and it establishes the existence of price dispersion in online marketplaces and offers a comparison with price dispersion in shop-bots. It is determined that online marketplaces may have less variation than on shop-bots, yet the price dispersion is still high. Chapter 3 is the second study and it explains much of the dispersion found in the online marketplace through differences in seller service quality and seller reputation. A seller's reputation was found to be the key contributor to variation in the online marketplace hence, study 3, which is chapter 4 of this dissertation, employs an experimental approach designed to offer a perspective of buyers and sellers to determine why price varies with reputation and if consumers value the reputation score. It was determined that buyers prefer sellers with strong long run reputation scores more than sellers with strong short-term reputation scores. Based on these reputation scores sellers want to try to offer a higher price than consumers are willing to pay, and sellers think that a strong score conveys higher levels of trust than buyers believe. This mismatch between how sellers think consumers respond, and how the consumers actually respond could be another driver of price dispersion online. A discussion of the implications of these research studies is offered in Chapter 5. / Business Administration