The Effect of Knowledge Sharing Using Customer Relationship Management Systems in Manufacturing Companies

This study assesses the influence on knowledge sharing among workers within Polish manufacturing enterprises. The study focuses on those workers who are involved within a company in a New Product Development (NPD) Process and who share their knowledge using the Customer Relationship Management (CRM) systems. The outcome based on the data obtained from Polish enterprises suggests that the use of the following functionalities of CRM system by workers: the Customer Profitability Database, the daily/weekly/monthly Customer Contact Database and the Customer Requirement Database focusing on services, affects knowledge sharing and increase the creation of new products. This case study investigates how useful that knowledge is which has been achieved using CRM systems and it clarifies its effect in Polish manufacturing enterprises

Products and Services

Today’s global economy offers more opportunities, but is also more complex and competitive than ever before. This fact leads to a wide range of research activity in different fields of interest, especially in the so-called high-tech sectors. This book is a result of widespread research and development activity from many researchers worldwide, covering the aspects of development activities in general, as well as various aspects of the practical application of knowledge

Factors affecting the agility of firms implementing lean manufacturing.

Master of Commerce in Management. University of KwaZulu-Natal, Pietermaritzburg 2015.Production methods lie on a continuum from mass production to Lean and or Agile. Agile production represents an innovative supply chain strategy that shows promise in the manufacturing sector. Many South African companies are not yet aware of Agility. Currently, many manufacturers are implementing Lean and JIT principles. However, Lean and JIT may not respond adequately to modern market demands and shortened product lifecycles. The Agile paradigm focuses on speed, flexibility and response: critical factors that enable companies to achieve a higher level of differentiation. The aim of this research was to determine the influence of different levels of Lean implementation on production Agility. This study was an innovative investigation into whether Lean and JIT contribute to, or detract from, Agility in manufacturing. There is little published research on this relationship. The study seeks to contribute to the body of knowledge and to benefit manufacturing companies: particularly those in South Africa. The research was exploratory in nature and consequently a case study approach was used. A non-probability, purposive sampling design was used to select three companies representing different categories on the spectrum of the Lean manufacturing continuum: Company A – beginner, Company B – intermediate and Company C – expert. The research was qualitative in nature. A review of the literature tends to suggest that Lean and JIT restrict Agility by restricting speed, flexibility and response. Contrary to expectations, the findings of the study indicate that Agility tends to increase in companies that have undertaken the Lean journey. The results of the study confirm that Lean contributes to Agility within the manufacturing sector. As Lean levels increase from beginner to expert so too do the levels of speed, flexibility and response (SFR). The conclusion drawn from this study is that Lean is a pre-requisite for Agile and companies may need to implement Lean before considering Agile systems. The results of this study have been used to construct a conceptual framework and road map that may be used by firms wishing to undertake the Agile journey. The strategy has been termed ParaLeagile and it may assist manufacturing companies to make more informed and appropriate decisions, thus boosting the economy

The case of internationalizing banks and the knowledge transfer process

Central to this thesis is the examination of cross border knowledge transfer mechanisms in multinational banks from emerging and advanced economies. Applying the Knowledge Based View, the Network theory, and Springboard perspective, this study advocates that exploiting and optimising knowledge synergies between subsidiaries located in different countries through knowledge transfer mechanisms is what is facilitating knowledge transfer for both multinational banks from emerging and advanced economies. By identifying and operationalizing knowledge transfer mechanisms in multinational banks, the research proves that emerging economy multinational firms do benefit from cross border knowledge mobility, and that knowledge transfer mechanisms exist in services multinational enterprises. Secondments and Communities of Practice have been identified as knowledge transfer mechanisms for an emerging economy multinational bank, while Global Job Postings and The Commercial Banking Corporate School have been identified as knowledge transfer mechanisms for an advanced economy multinational bank. The work suggest that the Network theory applies more to advanced economy multinational banks; that they do benefit more from their multinational network than emerging economy multinational banks

Strategic innovation, customer relationship management and the performance of SMEs' in Yemen: the moderating role of intellectual capital

The current study is the culmination of a number of years of research in the field of intellectual capital (IC), strategic innovation (SI) and customer relationship management (CRM) in relation to the pursuit of high performance in small and medium enterprises (SMEs). Against the background of the general theme, there is critical discussion of the performance of manufacturing SMEs in developing countries, in both theory and practice. This synthesis has led to a deeper understanding of the whole topic. Specifically, the current study fills the existing gaps in theory and practice by investigating the nature of the relationship between CRM, SI and SMEs' performance in the manufacturing industry of Yemen. It examines the moderating effects of IC on the relationship between CRM and SI and SME performance. A study relating IC and SI, CRM and SMEs' performance was designed. The survey method was used to collect data from 284 SMEs in the manufacturing industry of Yemen. Partial Least Squares-Structural Equation Modelling (PLS-SEM) was used to test the study's hypotheses. Results indicate that only three dimensions of CRM have a significant effect on SMEs' performance. SI has a significant effect on performance. The moderating effects of IC dimensions on the relationship between CRM dimensions and SI and SMEs' performance were examined. Results indicate that IC moderates the relationship between SI and finn performance; it also moderates the relationship between two CRM dimensions, technology based CRM (TCM) and CRM organization (CRMO) but not that between key customer focus (KCF) and CRM know ledge management (KM) and SME performance. The findings of this study offer important insights for owners and managers of SMEs, researchers and policymakers to further understand the effects of SI, IC and CRM on SMEs' performance. SMEs should also be encouraged to develop their CRM, SI and IC to improve their performance

Open Innovation in Micro, Small and Medium-Sized Enterprises

This book unveils the importance of micro, small, medium, and large firms for fostering open innovation, using methodological designs based on both qualitative and quantitative approaches. Several dimensions of the inbound and outbound open innovation strategies and practices are explored, in the scope of University–University, University–Industry, and University–Society relations

The Adoption of Emerging Technologies in Canada and their Impact on Innovation Performance

RÉSUMÉ: Bien que de nombreuses études aient exploré le rôle de l’adoption de la technologie sur l’innovation et le rendement des entreprises, toutes se sont concentrées sur quelques technologies et sur une catégorie en particulier. Les avantages de leur adoption ont été démontrés par de nombreux chercheurs et comprennent notamment l’augmentation de la productivité, une meilleure qualité des produits, la réduction des coûts, une meilleure adaptation aux besoins des clients, etc. Dans cette thèse, nous examinons une liste exhaustive de technologies appartenant à 4 catégories principales: la chaîne d’approvisionnement, l’intelligence d’affaires ainsi que la fabrication de pointe, qui est normalement divisée en deux sous-catégories, la conception et la fabrication. Notre recherche explore ces technologies sous différents angles pour comprendre leur effet sur la propension à innover. Nous utilisons trois approches différentes pour analyser l’impact de ces technologies. Tout d’abord, nous examinons le nombre de technologies adoptées combinées à des pratiques d’innovation ouverte qui auraient un effet sur la propension à innover. Pour estimer ces facteurs, nous utilisons une simple régression logistique. Parce que nous nous intéressons aux obstacles qui empêchent l’adoption, nous utilisons un modèle variable instrumental où nous considérons l’adoption des technologies comme endogènes. Les variables qui peuvent influer sur l’adoption de la technologie comprennent : les dépenses en immobilisations (CAPEX), les mesures de nombre adoptées pour contrer les obstacles ainsi que le recrutement d’employés liés à l’adoption de la technologie. La deuxième approche que nous utilisons est une analyse de panier de marché (MBA) utilisant l’algorithme apriori contenu dans une librairie R. Un MBA nous permet de trouver des complémentarités entre les technologies car les résultats montrent les faisceaux de technologies qui sont les plus populaires parmi les entreprises. En utilisant chaque famille de technologies, nous pouvons trouver ceux qui sont achetés ensemble le plus souvent. Enfin, en utilisant une autre libraire R (cspade), nous utilisons une autre approche qui ajoute une notion séquentielle à l’adoption. Non seulement nous pouvons trouver quelles technologies sont adoptées dans les mêmes faisceaux, mais nous pouvons également comprendre lesquelles sont adoptées en premier. L’enquête que nous utilisons fournit des informations sur le moment où une technologie a été adoptée (pour 3 ans, moins de 3 ans ou prévue dans les 3 prochaines années). Ces 3 timestamps sont essentiels pour comprendre que les entreprises adoptent les bons outils menant à des technologies émergentes telles que l’IdO et l’IA dans un proche avenir. Nos résultats montrent que le nombre de technologies adoptées a un impact significatif et positif sur la propension à innover, ce qui est vrai pour toutes les familles de technologies. En outre, les pratiques d’innovation ouverte telles que les alliances stratégiques et la collaboration avec les fournisseurs ont un impact positif sur la propension à innover, ce qui est similaire à ce qui a été trouvé dans des recherches antérieures. Le nombre de technologies adoptées a une incidence sur le nombre de mesures d’atténuation adoptées, un CAPEX plus élevé et sur le recrutement de nouveaux employés relatifs à l’adoption. Les trois variables ont un effet significatif et positif. Nous trouvons également des ensembles de technologies qui sont compatibles avec ce que nous avions prédit sur la base de notre examen technique exhaustif. Par exemple, des outils comme WMS (Warehouse Management System), Demand Forecasting (DF) et Customer Relation Management (CRM) constituent le faisceau le plus populaire lié aux technologies de la chaîne d’approvisionnement. Ce résultat a été prédit parce qu’il y a trois outils qui sont essentiels au processus de la chaîne d’approvisionnement qui permettent aux entreprises d’être efficaces lorsqu’elles prévoient la demande et gèrent les besoins des clients. Dans la catégorie Business Intelligence (BI), le groupe le plus populaire comprenait Software-as-a-service (SaaS) et Infrastructure-as-a-service (IaaS) avec plus de 27% des entreprises qui les adoptent. SaaS est particulièrement important pour les petites entreprises qui ne veulent pas construire une infrastructure pour gérer leurs besoins en technologies de l’information (TI). Dans les technologies de fabrication de pointe, ERP et MRPI ont été les groupes les plus populaires avec un taux d’adoption de 15%, tandis que les robots et le contrôle numérique informatique (CNC) ont été adoptés par 7% des entreprises. Malgré des taux d’adoption plus faibles dans le domaine de la fabrication, lorsque nous avons examiné les entreprises qui avaient l’intention d’adopter, nous avons remarqué que les technologies d’impression 3D étaient parmi les plus populaires. Nous voyons un résultat similaire lorsque nous examinons les technologies BI avec un logiciel de données massives (BDS), qui est une condition préalable pour rendre la mise en oeuvre de l’IA possible à l’avenir. Bien qu’en 2014 l’adoption du BDS ait été faible, nous constatons une augmentation constante lorsque nous analysons les entreprises qui prévoient l’adopter. En ajoutant une composante temporelle aux règles d’associations, il y avait entre 12% et 14% qu’une entreprise adopte un logiciel de données massives dans un temps futur. En combinant BDS et RTM en une seule technologie, le taux d’adoption d’une de ces deux technologies augmente à 40%. Une histoire similaire s’est dressée pour l’utilisation des imprimantes 3D. Lorsqu’elles sont considérées individuellement, le taux d’adoption futur est autour de 16%. Lorsqu’on considère au moins une des trois types d’imprimantes (3DP, 3DM ou 3DO), le taux d’adoption augmente à 33%, suggérant qu’une compagnie sur trois à l’intention d’adopter cette technologie dans le futur. Notre étude a des implications théoriques et pratiques. Premièrement, nous avons démontré que l’adoption de technologies de pointe peut avoir un effet endogène sur la propension à innover. Cet effet s’explique par le nombre de mesures d’atténuation adoptées pour contrer les obstacles à l’adoption, le CAPEX pour n’en nommer que quelques-uns. Nous avons également trouvé des faisceaux populaires de technologies qui sont adoptées ensemble. D’un point de vue théorique, c’est la première fois qu’une analyse du panier de marché (MBA) est utilisée pour comprendre le comportement des entreprises adoptant des technologies de pointe qui jouent un rôle dans l’amélioration des performances en matière d’innovation. D’un point de vue pratique, nous avons constaté que si les entreprises préfèrent acheter des technologies « à la carte », il existe encore des modèles émergents qui pourraient se traduire par des pratiques exemplaires pour les entreprises à la recherche de technologies qui peuvent le mieux servir leur coeur de métier.----------ABSTRACT: While many studies have explored technology the role of technology adoption on innovation and firm performance, there were all focussed on a few technologies and on one category in particular. The benefits of adopting them have been demonstrated by many scholars and include productivity increase, better product quality, cost reduction, better adaptation to customers’ needs, etc. This thesis explores an exhaustive list of technologies from four main categories: supply chain, business intelligence and analytics as well as advanced manufacturing, which is normally divided into two subcategories, design and fabrication. This research explores these technologies from various angles to understand their effect on the propensity to innovate. Three different approaches are used to analyze the impact of these technologies. First, the number of technologies adopted combined with open innovation practices that are thought to have an effect on the propensity to innovate are explored. To estimate these factors, a simple logistic regression is used. Because there is an interest in the obstacles that prevent adoption, an instrumental variable model is used, where the adoption of technologies is considered as endogenous. Variables that can affect technology adoption include capital expenditures (CAPEX), the number measures adopted to counter obstacles as well as the recruitment of employees pertaining to technology adoption. The second approach used is a market basket (MBA) analysis using the apriori library in R. A MBA allows to find complementarities between technologies because results show the bundles of technologies that are the most popular amongst firms. Using each family of technologies, it is possible to find the ones that are purchased together most often. Finally, using an additional R library (cspade), another approach that adds a sequential notion to the adoption is adopted. Not only it becomes possible to find which technologies are adopted within the same bundles, but understanding which ones are adopted first can also be studied. The survey provides information on when a technology has been adopted (for three years, less than three years or planned in the next three years). These three timestamps are crucial to understand companies are adopting the right tools leading to emerging technologies such as IoT and AI in the near future. The results show that the number of adopted technologies has a significant and positive impact on the propensity to innovate and this is true across all families of technologies. Furthermore, open innovation practices such as strategic alliances and collaboration with suppliers have positive impact on the propensity to innovate, which is what is similar to what was found in previous research. The number of adopted technologies is impacted by the number of mitigating measures adopted, a higher CAPEX and by the recruitment of new employees pertaining to the adoption. All three variables have a significant and positive effect. It should be noted that bundles of technologies that are consistent with what was predicted based on the exhaustive technical review were also found. For instance, tools like Warehouse Management System (WMS), Demand Forecasting (DF) and Customer Relation Management (CRM) form the most popular bundle related to supply chain technologies. This result was predicted because these three tools are core to the supply chain process that allows firms to be efficient when forecasting demand and managing customers’ needs. In the Business Intelligence (BI) category, the most popular bundle included software-as-a-service (SaaS) and Infrastructure-as-a-service (IaaS) with over 27% of firms adopting them. SaaS is particularly important for small companies that don’t want to build an infrastructure to manage their Information Technology (IT) needs. In the advanced manufacturing technologies, ERP and MRPII were the most popular bundles with 15% adoption rate while robots and Computer Numerical Control (CNC) were adopted by 7% of firms. Despite lower adoption rates in the manufacturing sphere, analyzing firms that planned to adopt suggested that 3D printing technologies were amongst the most popular. A similar result was observed for BI technologies with Big Data Software (BDS), which is a prerequisite to make AI implementation possible in the future. While in 2014, BDS adoption was low, there was a consistent increase in the adoption rate within the firms planning to adopt it. By adding the temporal dimension to the previous association rules, there were important elements that were discovered. The apparent increase in planned BDS adoption translated in a low probability of adoption (confidence between 12% and 14%) when taking time into consideration. However, assuming that BDS and RTM are the same technology, the probability of adopting either one of these technologies increases to about 40%. The same results were observed with 3D technologies, where 3DM and 3DP each had around 16% chance of being adopted in the future. Combining all 3D printing technologies as a single technology, this number increases to 33%, suggesting that 1 out 3 of firms planned to adopt additive manufacturing technologies sometime in the future. This study has some theoretical and practical implications. First, it was demonstrated that advanced technology adoption can have an endogenous effect on the propensity to innovate. This effect can be explained by the number of mitigating measures adopted to counter the obstacles to adoption, the CAPEX to name a few. Popular bundles of technologies that are adopted together were also observed. From a theoretical standpoint, it is the first time that a market basket analysis (MBA) is used to understand the behaviour of firms adopting advanced technologies that play a role in improving innovation performance. From a practical standpoint, it should be noted that while companies prefer to purchase technologies “à la carte”, there are still some emerging patterns that could translate into best practices for firms looking at which technologies are best suited to their core business

Knowledge and Management Models for Sustainable Growth

In the last years sustainability has become a topic of global concern and a key issue in the strategic agenda of both business organizations and public authorities and organisations. Significant changes in business landscape, the emergence of new technology, including social media, the pressure of new social concerns, have called into question established conceptualizations of competitiveness, wealth creation and growth. New and unaddressed set of issues regarding how private and public organisations manage and invest their resources to create sustainable value have brought to light. In particular the increasing focus on environmental and social themes has suggested new dimensions to be taken into account in the value creation dynamics, both at organisations and communities level. For companies the need of integrating corporate social and environmental responsibility issues into strategy and daily business operations, pose profound challenges, which, in turn, involve numerous processes and complex decisions influenced by many stakeholders. Facing these challenges calls for the creation, use and exploitation of new knowledge as well as the development of proper management models, approaches and tools aimed to contribute to the development and realization of environmentally and socially sustainable business strategies and practices