Optimal versioning strategy of enterprise software considering the customer cost-acceptance level

PurposeThe emergence of the Software-as-a-service (SaaS) licensing model dramatically changes how enterprise software is released. Especially, it is favored by small and medium enterprises (SMEs) because of the cost-friendly feature. In contrast, many large enterprises (LEs) own relatively abundant budgets and prefer the on-premise software to fulfill demands through customization. Considering the differentiated cost-acceptance level among customers, this study aims to address the versioning problem of the enterprise software faced by software firms.Design/methodology/approachA two-point distribution model is formulated to calculate the maximal profits software firm earned from both LEs and SMEs under three strategies (On-premise, SaaS and Hybrid). Then through profit comparison, this paper obtains the optimal versioning strategy and corresponding feasible conditions. Finally, the optimal solutions are derived concerning social welfare.FindingsA significant finding is that moving to SaaS becomes necessary for the software firms in product releases since the on-premise strategy will not be optimal. Based on this, this paper discovers that when LEs own a cost-acceptance level close to that of SMEs, the hybrid strategy is the only optimal choice. When LEs become less sensitive to costs, the hybrid strategy is suggested if the customization cost falls below the threshold. Otherwise, the SaaS strategy becomes the optimal option. The conclusions explain why some software vendors transit to “cloud companies” thoroughly and provide practical insights for software firms’ future decisions.Originality/valueTo the best of the authors’ knowledge, this paper is the first information economics study to consider consumer cost sensitivity in discussing enterprise software versioning. The differentiated cost-acceptance level is introduced to describe the customer utilities, and the results uncover the necessity of moving to SaaS under diversified customer composition. This work provides significant theoretical value and practical insights.

Redesigning the User-Interface: The Use of Colours in nopE-Commerce Enterprise Software

This paper appraises the relevance of e-commerce enterprise software in contemporary business management. Enterprise packages are technological applications that automate business activities and improve efficiency in the business workflow. The study enunciated the critical role of administrating the backend of enterprise software to manage the front-end which is accessible to users. The user interface of e-commerce enterprise backend is essential in enhancing user’s performance on the software. The study explores the psychological and physiological properties of colours in redesigning the nopE-commerce enterprise software for the backend user interface to enhance the efficiency of the administrators. The objectives of the study are to download the existing the backend of nopE-commerce enterprise software, to recreate the backend of nopE-commerce enterprise software and to introduce colours into the redesigned user interface backend of nopE-commerce enterprise software. The redesigned user-interface was subjected to the evaluation of one hundred (100) selected back-end administrators working in Lagos. The responses of participants were analysed using the 5-point Likert Scale to generate mean results. The results indicated that colours stimulate actions and feelings, user interface colours in virtual environment determines the efficiency of the system and the creative interplay of orange and blue colour in e-commerce back-end user interface enhances the performance of backend managers.

J.A.R.V.I.S Organizational Virtual Assistant

Chatbots, or conversational interfaces as they are also known, present a new way for individuals to interact with computer systems. Traditionally, to get a question answered by a software program involved using a search engine, or filling out a form. A chatbot allows a user to simply ask questions in the same manner that they would address a human. The most well known chatbots currently are voice chatbots: Alexa and Siri. However, chatbots are currently being adopted at a high rate on computer chat platforms. The technology at the core of the rise of the chatbot is natural language processing (“NLP”). A simple chatbot can be created by loading an FAQ (frequently asked questions) into chatbot software. The functionality of the chatbot can be improved by integrating it into the organization’s enterprise software, allowing more personal questions to be answered, like“When is the meet?”, or “What is the schedule of my day?”. A chatbot can be used as an “assistant” to a live agent, increasing the agent’s efficiency.

On Predicting Rediscoveries of Software Defects

The same defect may be rediscovered by multiple clients, causing unplanned outages and leading to reduced customer satisfaction. One solution is forcing clients to install a fix for every defect. However, this approach is economically infeasible, because it requires extra resources and increases downtime. Moreover, it may lead to regression of functionality, as new fixes may break the existing functionality. Our goal is to find a way to proactively predict defects that a client may rediscover in the future. We build a predictive model by leveraging recommender algorithms. We evaluate our approach with extracted rediscovery data from four groups of large-scale open source software projects (namely, Eclipse, Gentoo, KDE, and Libre) and one enterprise software. The datasets contain information about ⇡ 1.33 million unique defect reports over a period of 18 years (1999-2017). Our proposed approach may help in understanding the defect rediscovery phenomenon, leading to improvement of software quality and customer satisfaction.

On Predicting Rediscoveries of Software Defects

The same defect may be rediscovered by multiple clients, causing unplanned outages and leading to reduced customer satisfaction. One solution is forcing clients to install a fix for every defect. However, this approach is economically infeasible, because it requires extra resources and increases downtime. Moreover, it may lead to regression of functionality, as new fixes may break the existing functionality. Our goal is to find a way to proactively predict defects that a client may rediscover in the future. We build a predictive model by leveraging recommender algorithms. We evaluate our approach with extracted rediscovery data from four groups of large-scale open source software projects (namely, Eclipse, Gentoo, KDE, and Libre) and one enterprise software. The datasets contain information about ⇡ 1.33 million unique defect reports over a period of 18 years (1999-2017). Our proposed approach may help in understanding the defect rediscovery phenomenon, leading to improvement of software quality and customer satisfaction.

Competition Among Proprietary and Open-Source Software Firms: The Role of Licensing in Strategic Contribution

In enterprise software markets, firms are increasingly using services-based business models built on open-source software (OSS) to compete with established, proprietary software firms. Because third-party firms can also strategically contribute to OSS and compete in the services market, the nature of competition between OSS constituents and proprietary software firms can be complex. Moreover, their incentives are likely influenced by the licensing schemes that govern OSS. We study a three-player game and examine how open-source licensing affects competition among an open-source originator, an open-source contributor, and a proprietor competing in an enterprise software market. In this regard, we examine (1) how quality investments and prices are endogenously determined in equilibrium, (2) how license restrictiveness impacts equilibrium investments and the quality of offerings, and (3) how license restrictiveness affects consumer surplus and social welfare. Although some in the open-source community often advocate restrictive licenses such as the GNU General Public License because it is not always in the best interest of the originator for the contributor to invest greater development effort, such licensing can actually be detrimental to both consumer surplus and social welfare when it exacerbates this incentive conflict. We find such an outcome in markets characterized by software providers with similar development capabilities yet cast in favor of the proprietor. In contrast, when these capabilities either become more dispersed or remain similar but tilt in favor of open source, a more restrictive license instead encourages greater effort from the OSS contributor, leads to higher OSS quality, and provides a larger societal benefit. This paper was accepted by Chris Forman, information systems.