Social-Spatial Group Queries with Keywords

Social networks with location enabling technologies, also known as geo-social networks, allow users to share their location-specific activities and preferences through check-ins. A user in such a geo-social network can be attributed to an associated location (spatial), her preferences as keywords (textual), and the connectivity (social) with her friends. The fusion of social, spatial, and textual data of a large number of users in these networks provide an interesting insight for finding meaningful geo-social groups of users supporting many real-life applications, including activity planning and recommendation systems. In this article, we introduce a novel query, namely, Top- k Flexible Socio-Spatial Keyword-aware Group Query (SSKGQ), which finds the best k groups of varying sizes around different points of interest (POIs), where the groups are ranked based on the social and textual cohesiveness among members and spatial closeness with the corresponding POI and the number of members in the group. We develop an efficient approach to solve the SSKGQ problem based on our theoretical upper bounds on distance, social connectivity, and textual similarity. We prove that the SSKGQ problem is NP-Hard and provide an approximate solution based on our derived relaxed bounds, which run much faster than the exact approach by sacrificing the group quality slightly. Our extensive experiments on real data sets show the effectiveness of our approaches in different real-life settings.

Cloud service recommendation for small and medium-sized enterprises: A context-aware group decision making approach

Recently, the enormous advantages of cloud services make them increasingly appealing to the small and medium-sized enterprises. The growing number of available services makes it challenging to select trustworthy services. Existing approaches focus on user preferences to guide personalized services recommendation for individual users, but lack of the research on trustworthy service recommendation for the small and medium-sized enterprises that represents a group user consisting of multiple individual users. For this type of enterprise, the cloud services recommendation must address the challenges from the diverse client context of individual users, the imprecise quality of experience in an uncertain cloud environment and the invalid or unsatisfactory recommendations. A client context-aware approach is proposed to recommend trustworthy cloud services for the small and medium-sized enterprises based on non-compensatory multi-criteria decision-making. In it, a type of client context is viewed as an independent evaluation criterion, and the interval neutrosophic numbers are employed to measure the fuzzy trustworthiness of cloud services. Based on the investigated outranking relations of interval neutrosophic numbers, a non-compensatory multi-criteria decision-making procedure via an improved ELECTRE III method is developed to rank candidate services. Experimental results demonstrate that this approach could efficiently produces the accurate ranking results of cloud services and effectively recommend the trustworthy service for small and medium-sized enterprises.

Strategi pengembangan desa wisata osing dalam upaya pemulihan ekonomi pada masa pandemi Covid-19

This study tries to find a strategy for developing the Osing Tourism Village as an effort to recover the economy during the Covid-19 pandemic. This type of research is a combination (mix method) used in this study. The research location is Osing Tourism Village in Banyuwangi Regency with the target group being a tourism-aware group that manages Osing Tourism Village. The time for collecting research data is in the period June - September 2021. Based on the results of the data obtained, four strategies are produced that can be used for the development of the Osing tourism village. First, optimizing the improvement of the image and branding of the Osing Indigenous Tourism Village so that it remains the choice of tourist destination in the New Normal era. Second, increasing the capacity of human resources for tourism actors in the use of digital technology facilities to support tourism during the Covid-19 pandemic. Third, changing the trend of tourism into technology-based tourism in terms of product marketing and tourism management. To bring the Osing tourism village to life through product innovations that are preferred by consumers with attractive and contemporary packaging models. Fourth, collaborate with the private sector and local governments in providing facilities and infrastructure to support tourism activities during the Covid-19 pandemic.

Profiling Spanish Prospective Buyers of Electric Vehicles Based on Demographics

As traffic congestion and air pollution rise at alarming rates in many cities worldwide, new smart technologies are emerging to meet the urban mobility challenge. In addition, automotive firms have transformed their business models to make them more sustainable and to adjust to demand response. Electric vehicles (EVs) represent a viable option to reduce ecological damage and improve public health. However, in the previous literature, no consensus has been reached on the profile of prospective buyers of EVs. Based on a large-scale sample of Spanish citizens and using cluster analysis, our study provides a better understanding of the demographics of such prospective buyers. We identified four types of EV prospective buyers. Our results show that although men have a strong preference for EVs, low-income older women prove to be the most EV-aware group; their automotive driving experience and concern for sustainability could be among the underlying causes of this particular interest. Another valuable insight is the greater partiality of older people for EVs. These findings have many implications for managers, especially in the automotive industry, policymakers, and sustainability strategists. They show that EV prospective buyers should not be approached as a homogeneous group but as a heterogeneous group with different socio-demographic characteristics that might help decision-makers make better business decisions.

Tourism village development study: Lesson learned from Flory Village, Sleman Regency, Yogyakarta

Flory Village is one of the tourism villages based on ecotourism in Sleman Regency. The formation of Flory Village is inseparable from the role of tourism aware group (Pokdarwis). The existence of village tourism destinations has a positive impact on rural economic development and regional tourism. This study explores how Flory Village and the community manage tourism. This research used descriptive qualitative which were analyzed using the Miossec model through the components of transportation, facilities, attitudes towards tourists, and the role of stakeholders. The result is that there are two tourism village groups, namely Dewi Flory and Taruna Tani who have succeeded in developing their tourism potential based on their respective characteristics. Dewi Flory focuses on educational tourism, making salted eggs, nata de coco, vegetable gardening, and outbound tourism in three rides: water rides, dry rides, and mini forests. Furthermore, Taruna Tani focuses on agriculture, such as ornamental plants and fruits, and village culinary tours. The four lessons from the management of a tourism village by two Pokdarwis in Flory Village are consistent innovation, management commitment, utilization of local human resources, and collaboration with other parties.