Characterizing business models for digital business through patterns

This article considers business models through the lenses of both design science and the design orientation in management. It describes a new way of thinking about and engaging with business models as patterns. The term “business pattern” is used to refer to a coherent and repeating sequence of action involving humans, machines (including information technologies systems) and artifacts (such as data structures) as a way of organizing a firm. The study also describes a way of visualizing either existing business patterns or envisaged business patterns through the design artifact of a pattern comic. This is used to provide a narrative of some business pattern in principle or in practice. The design theory of a business pattern as well as the design artifact of a pattern comic offer a range of contributions to the literature on business models. First, they permit a clearer distinction to be drawn between business model, business motivation, and business strategy. Second, they suggest a clearer way of building models of “business” (organizing) either as currently conceived (as-is) or in terms of envisaged models (as-if). This also allows clearer expression of business motivation in terms of transitions between as-is and as-if business patterns. Third, business patterns offer a practical way of thinking about the reuse of business models as patterns and their potential for benchmarking purposes. To help ground both the theorization and the visualization proposed we apply the design theory of a business pattern and the design artifact of pattern comics to help make sense of the domain of online grocery

The impact of Digital Platforms on Business Models: an empirical investigation on innovative start-ups

Digital platforms have the ability to connect people, organizations and resources with the aim of facilitating the core interactions between businesses and consumers as well as assuring a greater efficiency for the business management. New business concepts, such as innovative start-ups, are therefore created based on innovation, scalability and the relationships within the community around them. The purpose of this work is to deeply understand the evolution of business models brought by innovative and dynamic companies operating through online platforms. In order to achieve the objectives set, an exploratory multiple-case study was designed based on in-depth structured interviews. The aim was to conduct a mixed analysis, in order to rely both on qualitative and quantitative data. The structured interview protocol was therefore designed to collect and then analyse data concerning the company profile and managers’ perspectives on the phenomenon of interest. The interview protocol was submitted in advance and then face-to-face interviews were carried out with the following professional figures: Chief Executive Officer (CEO), General Manager, Chief Technology Officer (CTO), Marketing Manager and Developers. Collected data were analysed and processed through the Canvas Business Model in order to clearly outline similarities and differences among the sample. Results can be considered under two viewpoints. On the one hand, this work provides a detailed overview of the companies interviewed, according to the dimensions of: reference market dynamics, type and number of customers, scalability. On the other one, they allow to identify some success patterns regarding key activities, key resources, channel mix strategy, costs management, value proposition, customer segmentation, key partners and the way to obtain revenues. Results from the multiple-case study with 15 Italian start-ups provide interesting insights by comparing the innovative business models developed and highlighting key differences and similarities. verall, the start-ups analyzed, operating in several sectors, showed great growth prospects and the possibility to create value for their customers through innovative products and services offered through digital platforms

Understanding Mobile Traffic Patterns of Large Scale Cellular Towers in Urban Environment

Understanding mobile traffic patterns of large scale cellular towers in urban environment is extremely valuable for Internet service providers, mobile users, and government managers of modern metropolis. This paper aims at extracting and modeling the traffic patterns of large scale towers deployed in a metropolitan city. To achieve this goal, we need to address several challenges, including lack of appropriate tools for processing large scale traffic measurement data, unknown traffic patterns, as well as handling complicated factors of urban ecology and human behaviors that affect traffic patterns. Our core contribution is a powerful model which combines three dimensional information (time, locations of towers, and traffic frequency spectrum) to extract and model the traffic patterns of thousands of cellular towers. Our empirical analysis reveals the following important observations. First, only five basic time-domain traffic patterns exist among the 9,600 cellular towers. Second, each of the extracted traffic pattern maps to one type of geographical locations related to urban ecology, including residential area, business district, transport, entertainment, and comprehensive area. Third, our frequency-domain traffic spectrum analysis suggests that the traffic of any tower among the 9,600 can be constructed using a linear combination of four primary components corresponding to human activity behaviors. We believe that the proposed traffic patterns extraction and modeling methodology, combined with the empirical analysis on the mobile traffic, pave the way toward a deep understanding of the traffic patterns of large scale cellular towers in modern metropolis.Comment: To appear at IMC 201