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In spite of the fact that public procurement is increasingly becoming a popular technique for small business empowerment, there are various challenges facing SMEs in public procurement. Using Nigeria as a platform, this paper examines barriers that hinder SMEs access to public procurement markets. Data were collected from literature review, analysis of documents and semi-structured interviews. The results show that lack of transparency in tendering often discourages SMEs from getting involved in public procurement in Nigeria. It further highlights the need for actions to address issues facing SMEs at different stages of the procurement process. By integrating research findings into existing knowledge, a taxonomy of techniques for enhancing SMEs access to public procurement is proposed. The taxonomy reveals specific schemes and measures to promote SME participation in public procurement. This will offer guidance to governments, policy makers and procurement experts on the implementation of SME-friendly procurement practices. The study adds to the on-going debates on the significance of public procurement policy on SME development.

This research work investigates the simultaneous interaction of entrepreneurial orientation dimensions of the firm with the leader’s psychological factors for a better explanation of SMEs’ performance. The universal and contingency approach are reductionist and do not allow us to achieve the research objective. So, to study the simultaneous interaction between a great number of variables, we are mobilizing for this purpose the configurational approach and particularly, the perspective of alignment (fit) as “configuration”. Indeed, we are pursuing a quantitative methodological approach and conducting a field survey through a research questionnaire distributed to 100 industrial Tunisian SMEs.

The results of this research reveal a taxonomy of four configurations of industrial Tunisian SMEs significantly different from each other and which have different effects on performance. The configurations are named, the “Leader”, the “Creative”, the “Ambitious” and the “Conservative”.

Grand Challenges in Biodiversity Informatics.

Using Biodiversity Information Effectively.

By 2018, business analytics (BA), believed by global CIOs to be of strategic importance, had for years been their top priority. It is also a focus of academic research, as shown by a large number of papers, books, and research reports. On the other hand, the BA domain suffers from several incorrect, imprecise, and incomplete notions. New areas and concepts emerge quickly; making it difficult to ascertain their structure. BA-related taxonomies play a crucial role in analyzing, classifying, and understanding related objects. However, according to the literature on taxonomy development in information systems (IS), in most cases the process is ad hoc. BA taxonomies and frameworks are available in the literature; however, some are excessively general frameworks with a high-level conceptual focus, while others are application or domain-specific. Our paper aims to present a novel semi-automatic method for taxonomy development and maintenance in the field of BA using content analysis and text mining. The contribution of our research is threefold: (1) the taxonomy development method, (2) the draft taxonomy for BA, and (3) identifying the latest research areas and trends in BA.

Businesses today, including non-profits, recognise the need for knowledge management (KM). KM may require new strategies and goals before it can be implemented, or it can be aligned with current business strategies for quicker implementation. The framework presented here is for managers in companies and organisations to use to align their KM strategies with business strategies to improve performance involving financial growth, cost reduction and customer satisfaction. A study of three strategic types of organisations (defender, prospector, analyser) and interviews at a large corporation and a non-profit organisation suggests that the conceptual framework presented in this paper can be verified. More empirical evidence of alignment is planned, as organisations become more sophisticated users of KM.

The authors have been working for over three years on the taxonomy and conceptual framework for KM/BS Alignment (also known as KMSABS) and present a procedure for implementation in this paper. The KM/BS Alignment model involves concepts, actors, actions and processes. An important aspect of the methodology is for businesses and organisations to identify their strategic character to support appropriate interactions associated with knowledge. As shown in this paper, product and knowledge managers can affect goal alignment and interaction in an organisation if they implement change based on the suggested framework.

The study of production systems taxonomy not only provides a good description of organization dominant groups but also provides the ground for more specialized studies such as a study of performance, the proper form of production decisions in each group, and the theorizing in it. In some taxonomic studies, due to high speed and ease of implementation, K-means cluster analysis was used to analyze data but the convergence took place in local optimum. For this reason, Hybrid Clustering Algorithms were used for the clustering of manufacturing companies. The clustering results of these methods were compared using validation indicators. According to the results of the comparisons, the best clustering algorithm was chosen, based on which cluster naming was done. Then, using the results of Discriminant Analysis, the distinctive dimensions of clusters were identified and the results showed that the manufacturing systems in Iran can be introduced in two dimensions of green production planning and resource capacity.

Artificial intelligence (AI) serves as a technological driver for business model innovation by guiding decisions and automating services, thereby leveraging efficiency-enhancing and profitable business practices. Especially in the electric power industry, a multitude of start-ups have entered the market offering disruptive AI-based services. However, there has been little research to date on what concrete business models result from the diffusion of AI and how these might be classified. In view of this research gap, this paper contributes to a better understanding of start-ups in the electric power industry that use AI technologies by systematically developing a business model taxonomy. In addition, we conducted 12 semi-structured interviews with domain experts for the evaluation step and validated the robustness of the taxonomy based on cluster analysis to identify common business model archetypes. Finally, we derived and discussed the academic and practical implications of our research and highlighted future research avenues.

Do SMEs cluster around different types of innovation activities? Are there patterns of SME innovation activities? To investigate we develop a taxonomy of innovation activities in SMEs using a qualitative study, followed by a survey. First, based upon our qualitative research and literature review we develop a comprehensive list of innovation activities SMEs typically engage in. We then conduct a factor analysis to determine if these activities can be combined into factors. We identify three innovation activity factors: R&D activities, incremental innovation activities and cost innovation activities. We use these factors to identify three clusters of firms engaging in similar innovation activities: active innovators, incremental innovators and opportunistic innovators. The clusters are enriched by validating that they also exhibit significant internal similarities and external differences in their innovation skills, demographics, industry segments and family business ownership. This research contributes to innovation and SME theory and practice by identifying SME clusters based upon their innovation activities.

A stream of servitisation research has focused on the construction of taxonomies and typologies of product–service system business models (BMs). However, their relevance in the context of increased utilisation of digital technologies may be questioned. Thus, the purpose of this paper is to empirically revisit the existing product–service system BM taxonomies to explore the following research question: How can the BMs of servitised manufacturing firms be categorised in the digital era? The question is addressed through an embedded case study of five servitised firms. We found that the firms’ BMs varied with regard to the degree of the suppliers’ ownership of delivered products, degree of smartness of the services provided and degree of performance orientation of contracts. Based on these findings, we derived a new product–service system BM taxonomy with eight categories, presented in a 2 × 2 × 2 matrix, that significantly extends earlier taxonomies.

Previous studies often assume that business model innovation (BMI) is reflected in an entrepreneurial business model design. We assume that business model reconfiguration (BMR) takes place in more nuanced types and does not always lead to (radical) BMI. By undertaking a mixed methods study with 213 respectively 16 SMEs from the electronic industry, we uncover six basically different types of BMRs and discuss their performance implications. By this, we shape the current understanding of BMR and shed light on variety and implications of different types of BMRs. Our configuration study indicates that firms achieve superior performance when implementing a radically new business model reflected in a new configuration of all three components of the business model: value creation, value proposition, and value capture. Second, BMR can take place in types where only some parts of the business model are extensively changed, while others are only slightly adapted.

Do SMEs cluster around different types of innovation activities? Are there patterns of SME innovation activities? To investigate we develop a taxonomy of innovation activities in SMEs using a qualitative study, followed by a survey. First, based upon our qualitative research and literature review we develop a comprehensive list of innovation activities SMEs typically engage in. We then conduct a factor analysis to determine if these activities can be combined into factors. We identify three innovation activity factors: R&D activities, incremental innovation activities and cost innovation activities. We use these factors to identify three clusters of firms engaging in similar innovation activities: active innovators, incremental innovators and opportunistic innovators. The clusters are enriched by validating that they also exhibit significant internal similarities and external differences in their innovation skills, demographics, industry segments and family business ownership. This research contributes to innovation and SME theory and practice by identifying SME clusters based upon their innovation activities.

This study presents a novel taxonomy of short message service campaigns, for the purpose of building an intelligent marketing system. The main issue of mass marketing is that one size does not fit everybody. In other words, it is challenging to meet different consumer needs. With the help of artificial intelligence, marketers can be supported to overcome some of these challenges. This study uses a mixed methods approach where design science and grounded theory is used to produce a short message service campaign taxonomy for a future intelligent marketing system. Data collection consisted of 386 previously active campaigns used over 33 months to build the taxonomy. An experimental study was conducted to test the effectiveness of the proposed taxonomy. The experiments involved automatic generation of campaign messages. The validity of these campaign messages, and hence the proposed taxonomy, was ascertained by analysing the messages within a business context. The study concludes that the system, intertwined with the taxonomy, performs comparably to a regular campaign. Another proof of concept is that the business context deemed the generated campaign texts to be both semantically and syntactically similar to run them in active campaigns as experiments.

This paper reviews collaborative technologies from cutting-edge research projects that support the intelligence analysis. Using the collaboration in knowledge management literature as reference point, a content analysis of representative documents of intelligence collaboration systems reveals three major components of collaborative technologies (knowledge discovery, decision-making tools, and collaborative environment), together with the dimensions of agents and time. The empirical-based taxonomy applied to intelligence collaboration work is demonstrated. The potential areas of application of question representation in information retrieval and knowledge-based systems, and the applicability of a collaborative information retrieval search tool as inputs to decision-making tools are discussed.