Rating system in Food delivery

A small business in food delivery has much competition. The organisation delivers food in food trucks at local markets. The aim of this research is to examine how a rating system will impact on the quality of goods and services and customer satisfaction levels. This research will accomplish the aim in three steps: examine the current state of food trucks, investigate the potential of a rating system, and identify further avenues to use rating systems efficiently. A survey of customers will be used to gather quantitative data and an interview to gather qualitative data

The Lascar groups and the 1st homology groups in model theory

Let $p$ be a strong type of an algebraically closed tuple over B=\acl^{\eq}(B) in any theory $T$. Depending on a ternary relation \indo^* satisfying some basic axioms (there is at least one such, namely the trivial independence in $T$), the first homology group $H^*_1(p)$ can be introduced, similarly to \cite{GKK1}. We show that there is a canonical surjective homomorphism from the Lascar group over $B$ to $H^*_1(p)$. We also notice that the map factors naturally via a surjection from the `relativised' Lascar group of the type (which we define in analogy with the Lascar group of the theory) onto the homology group, and we give an explicit description of its kernel. Due to this characterization, it follows that the first homology group of $p$ is independent from the choice of \indo^*, and can be written simply as $H_1(p)$. As consequences, in any $T$, we show that $|H_1(p)|\geq 2^{\aleph_0}$ unless $H_1(p)$ is trivial, and we give a criterion for the equality of stp and Lstp of algebraically closed tuples using the notions of the first homology group and a relativised Lascar group. We also argue how any abelian connected compact group can appear as the first homology group of the type of a model.Comment: 30 pages, no figures, this merged with the article arXiv:1504.0772

Informational Complexity and the Flow of Knowledge across social boundaries

Scholars from a variety of backgrounds – economists, sociologists, strategists, and students of technology management – have sought a better understanding of why some knowledge disperses widely while other knowledge does not. In this quest, some researchers have focused on the characteristics of the knowledge itself (e.g., Polanyi, 1966; Reed and DeFillippi, 1990; Zander and Kogut, 1995) while others have emphasized the social networks that constrain and enable the flow of knowledge (e.g., Coleman et al., 1957; Davis and Greve, 1997). This chapter examines the interplay between these two factors. Specifically, we consider how the complexity of knowledge and the density of social relations jointly influence the movement of knowledge. Imagine a social network composed of patches of dense connections with sparse interstices between them. The dense patches might reflect firms, for instance, or geographic regions or technical communities. When does knowledge diffuse within these dense patches circumscribed by social boundaries but not beyond them? Synthesizing social network theory with a view of knowledge transfer as a search process, we argue that knowledge inequality across social boundaries should reach its peak when the underlying knowledge is of moderate complexity. To test this hypothesis, we analyze patent data and compare citation rates across three types of social boundaries: within versus outside the firm, geographically near to versus far from the inventor, and internal versus external to the technological class. In all three cases, the disparity in knowledge diffusion across these borders is greatest for knowledge of an intermediate level of complexity.evolutionary economics, informational complexity, knowledge flow, social boundaries

How a rating system impacts on the quality of goods and services and satisfaction level of customers.

This research report is starting with presenting about the aim of examining ways to satisfy food truck customers with rating system by examining the current status of food truck businesses, investigating the potential of a rating system and generate further revenue to use a rating system. This report is presenting in order of organisation context, literature review, methods, results, discussion, conclusion, and recommendations. Mixed method is used for this research. For quantitative research, both online and offline survey were used. Result and discussion from them are presented by three topics: the popularity of food trucks, perception about food trucks and opinions about ‘Rating system’. For qualitative research, an interview was used. Result and discussion from it also presented by three topics: status of ‘Rating system’, perception about ‘Rating system’ and intention of showing ratings off to customers. Lastly, there are three recommendations covered in this research: collaborating with Ministry of Primary Industries, application of ‘Rating system’ and use of social media