Abstract
In celebration of the 10th anniversary of the International Conference on Exploring Service Science (IESS), this paper takes a historical look at the papers that have been published in the IESS proceedings. The analysis is focused on the development and evolution of the IESS community and of the main research topics covered by the published papers over time. The IESS community is portrayed in terms of authors, their affiliations and co-authoring network, while the topics are analyzed according to the papers' keywords. Moreover, this paper analyzes the impact of the papers published in this decade, in terms of citations. These results are then discussed in light of the observed trends and of the evolution of the service science field, to guide the future development of the IESS conference and of research on service science.

Abstract
Although interest in FinTech businesses has been growing, research about these companies is still scarce. To address this gap, this paper aims to understand the evolution of the FinTechs ecosystem, through a socio-technical system theory and service innovation lense. A case study research methodology was used, in which 6 Brazilian and 5 Portuguese FinTechs were analyzed. Primary data was collected using semi-structured interviews with managers and employees of the startups, while secondary data was obtained through the analysis of reports from consulting firms and public relations materials of the startups. Results show the evolution of FinTech ecosystems from the perspective of socio-technical system theory and service innovation. From the socio-technical system perspective it was possible to understand the roles of social, technological and organizational actors in the evolution of these ecosystems. From the service innovation perspective, it was possible to understand the dynamics of the evolution of the FinTech ecosystems and its results.

Abstract
Purpose This article provides an in-depth understanding of customer experience with smart services, examines customer perceptual responses to smart and connected service environments and enriches this understanding by outlining how contextual factors (in terms of goals, activities, actors and artifacts) influence the customer experience. Design/methodology/approach This study adopts a qualitative approach in order to understand customer experience in the smart energy service setting. Semi-structured interviews and focus groups were conducted with 31 participants forming three groups of energy service customers: advanced smart energy (ASE) customers, electric mobility (EM) customers and high-consumption (HC) customers. Findings The findings show that customer experience with smart services involves a multidimensional set of perceptual responses, comprising specific smart service dimensions (e.g. controllability, visibility, autonomy); relationship dimensions (relationships with the service provider and with the community); and traditional technology-enabled service dimensions (e.g. ease of use, accessibility). The analysis of contextual factors such as goals, activities, actors and artifacts shows that smart services enable a more autonomous experience, wherein customers can integrate a myriad of actors and artifacts and expect the main service provider to support them in taking the lead. Originality/value Smart technologies have profoundly changed the service environment, but research on customer experience with smart services is scarce. This study characterizes smart services, provides an in-depth understanding of customer experience in this new context, and discusses relevant implications for management and service research.

Abstract
There are extensive studies in the literature about the reorder point/order quantity policies for inventory management, also known as policies. Over time different algorithms have been proposed to calculate the optimal parameters given the demand characteristics and a fixed cost structure, as well as several heuristics and meta-heuristics that calculate approximations with varying accuracy. This work proposes a new meta-heuristic that evolves closed-form expressions for both policy parameters simultaneously - Cooperative Coevolutionary Genetic Programming. The implementation used for the experimental work is verified with published results from the optimal algorithm, and a well-known hybrid heuristic. The evolved expressions are compared to those algorithms, and to the expressions of previous Genetic Programming approaches available in the literature. The results outperform the previous closed-form expressions and demonstrate competitiveness against numerical methods, reaching an optimality gap of less than , while being two orders of magnitude faster. Moreover, the evolved expressions are compact, have good generalisation capabilities, and present an interesting structure resembling previous heuristics.

Abstract
The synchronization of Public Transportation (PT) systems usually considers a simplified network to optimize the flows of passengers at the principal axes of the network. This work aims to identify the most relevant transfer-connections in a PT network. This goal is pursued with the development of a methodology to identify relevant transfer-connections from entry-only Automatic Fare Collection (AFC) data. The methodology has three main steps: the implementation of the Trip-Chaining-Method (TCM) to estimate the alighting stops of each AFC record, the identification of transfers, and finally, the selection of relevant transfer-connections. The adequacy of the methodology was demonstrated with its implementation to the case study of Porto. This methodology can also be applied to PT systems using entry-exit AFC data, and in that case, the TCM would not be required.

Abstract
The negative impacts of urban logistics have fostered the search for new distribution systems in inner city deliveries. In this context, interesting solutions can be developed around two-echelon distribution systems based on mobile depots (2E-MD), where loads arriving from the periphery of the city are directly transferred, at intermediate locations, from larger to smaller vehicles more suited to operate in the city centre. Four types of 2E-MD can be identified, according to the degree of mobility of larger vehicles and their accessibility to customers. In this paper, we propose a generic three-index arc-based mixed integer programming model, for a two-echelon vehicle routing problem, with synchronisation at the satellites and multi-trips at the second echelon. This generic base model is formulated for the most restrictive type of problems, where larger vehicles visit a a single transfer location and do not perform direct deliveries to customers, but it can be easily extended to address the other types of 2E-MD. The paper presents how these extensions account for the characteristics of the different types of 2E-MD. The generic model, its extensions and the impact of a set of valid inequalities are tested using problem instances adapted from the VRP literature. Results show that the proposed extensions do adequately address the specific features of the different types of 2E-MD, including multiple visits to satellites, and direct deliveries to customers. Nevertheless, the resulting models can only tackle rather small instances, even if the formulations can be strengthened by adding the valid inequalities proposed in the paper. © 2020 The Authors. Published by ELSEVIER B.V.