Group work and online discussions are not new terms in education and are important activities for Information Systems students. It has become important because it encourages creative thinking and provides more efficient problem-solving approaches. Online social networking sites, like Facebook, have pedagogical potential and the consideration of its academic application should not be ignored by lecturers or students. The main problem identified in this thesis is that the awareness and application of the emerging pedagogical potential of online social networking sites, like Facebook, especially for the purpose of group work and online discussions, is limited among Information Systems lecturers and students. The purpose of this study is to determine the level of awareness and application of Facebook as an academic tool by Information Systems lecturers and students, and whether it can enhance the learning experience of students, related to the effectiveness of group work and online discussions. The perceptions of both Information Systems lecturers and students were recorded by means of questionnaires and interviews. It was found that most lecturers and students were aware of Facebook’s pedagogical potential. However, the consideration and application of Facebook as an academic tool, by lecturers and students, are limited. From a cultural perspective, it was found that students from a private institution, where no Learning Management System was implemented, as well as black students, showed increased levels of utilisation and performance, in terms of enhanced learning experienced, on the academic groups on Facebook. The researcher developed a model for the academic application of Facebook for Information Systems students, based on the Task-Technology Fit and the Social Software Performance Model theories. This study concludes with the recommendation that Information Systems lecturers and students should become increasingly aware of and consider the pedagogical potential of Facebook as a supplementary tool and with suggestions for future research. / Dissertation (MCom)--University of Pretoria, 2010. / Informatics / unrestricted

The mobile banking is an increasingly popular service for customers of the traditional banking industry. On the surface, China has the highest adoption rate of this new technology, yet many users do not remain active or they only use mobile banking for the simplest tasks such as checking their balance. This research was designed to uncover the reasons for these two issues by identifying the major factors influencing users' intention to continue using mobile banking (continuance intention) as well as their behavioural intention to try new mobile banking functions. To do so, an integrated model was developed on the basis of the unified theory of acceptance and use of technology model (UTAUT), task-technology fit model (TTF) and expectation confirmation model (ECM). Empirical data were collected from China's mobile banking users and the integrated model was tested using Partial Least Squares Structural Equation Modelling (PLS-SEM) approach. The results indicate that the main factors which positively influence the continuance intention include satisfaction, performance expectancy and effort expectancy. Continuance intention, in turn, influences behavioural intention to try new functionality, together with social influence, facilitating conditions and confirmation. Moreover, some mediating effects were discovered. For example, task-technology fit may indirectly affect the continuance intention through users' satisfaction. The research results have a number of theoretical contributions. Firstly, this research discovers that the impact of task-technology fit on users' continuance intention towards mobile banking is fully mediated by users' satisfaction. This enriches the extant literature that is mostly focused on the technology perceptions (e.g. performance expectancy and effort expectancy) of users. Secondly, this research identifies that satisfaction also mediates the impact of confirmation of expectations on continuance intention, also extending the literature on the continuance usage of information systems. Thirdly, this research fills the gap in extant research regarding users' intention to try new mobile banking functions, by proposing a new integrated model using constructs from UTAUT, TTF, and ECM, and demonstrating that continuance intention itself fully mediates the impact of performance expectancy and effort expectancy on behavioural intention. The new model has a high explanatory power than each individual model offers. The research results also have management implications in terms of how to improve the task-technology fit to support continuous use and extended the use of mobile banking. For instance, to improve continuance intention banks can improve satisfaction by optimising task-technology fit. This in turn will require better understanding of users' different task requirements in specific market segments. In addition, banks can also attract users' behavioural intention to try new functionality by timely updating corresponding technology and launching marketing campaigns to keep users informed of any new functions of their mobile banking application.

Each year, 1.3 billion tons of food produced for human consumption are lost or go to waste globally throughout the food supply chain (FSC). Increasing the efficiency of the entire FSC is an essential action in achieving food security for the global population, which includes reducing the amount of food lost and wasted. This thesis aims to contribute with rich insight into if and how contemporary information systems in grocery stores, which are part of the FSC, are supporting expiration date tracking and if they are contributing to reducing food waste. The study was carried out as a case study in three grocery stores, applying the task-technology fit model as its theoretical framework to guide the study and analyze the empirical results. The study found that the expiration date tracking systems in the grocery stores supported them in tracking expiration dates considering the measurements of task-technology fit since they sufficiently support and fulfill the needs of the users’ tasks, but that there is still room for improvement. The study also found that, according to the users’ perceptions, the grocery stores using expiration date tracking systems were able to prevent more food waste when using the systems in comparison to if they would not have been used.

No description available.

<p>With the increasing prevalence of chronic disease throughout the world, electronic Personal Health Records (ePHRs) have been suggested as a way to improve chronic disease self-management. However, ePHRs are not yet widely used by consumers. Protection Motivation Theory (PMT) has been successfully used to explain health related behaviours among chronic disease patients. In addition, Information Systems (IS) theories such as Task Technology Fit (TTF) have been successfully used to explain information technology adoption. This study combines PMT with Perceived Task Technology Fit (PTTF) and the health self-management readiness concept of the Patient Activation Measure (PAM) to propose a research model which will aid in the understanding of ePHR adoption by chronic disease patients. The role of educational interventions on various elements of the proposed model is also examined. A survey-based study of 230 participants is used to empirically validate the proposed model via structural equation modeling techniques. Results reveal that the PMT constructs, as well as PTTF and PAM all have significant direct or indirect effects on the intention to adopt an ePHR. In addition, the educational intervention analysis indicates that the provision of advanced ePHR education positively influences various constructs in the model, while the use of fear appeals through Diabetes complication education does not have an effect.</p> / Doctor of Philosophy (PhD)

Involving customers in the creation and design process of new products and services has been dis-cussed in practice and research since the early 1980’s. As one of the first researchers, von Hippel (1986) shed light on the concept of Lead Users, a group of users who are able to provide most accu-rate data on future needs for organizations. Subsequently, many scholars emphasized different areas of contribution for customers and how they provide assistance to the process of innovation. First of all, customers may contribute to product innovation (Cooper & Kleinschmidt, 1987; Driessen & Hillebrand, 2013; Füller & Matzler, 2007; Gruner & Homburg, 2000; Sawhney, Verona, & Prandelli, 2005; Snow, Fjeldstad, Lettl, & Miles, 2011; Yang & Rui, 2009) and service innovation (Abecassis-Moedas, Ben Mahmoud-Jouini, Dell’Era, Manceau, & Verganti, 2012; Alam, 2002; Chesbrough, 2011; Larbig-Wüst, 2010; Magnusson, 2003; Paton & Mclaughlin, 2008; Shang, Lin, & Wu, 2009; Silpakit & Fisk, 1985), e.g., by co-creating values (Prahalad & Ramaswamy, 2004), such as concepts or designs as well as reviewing and testing them throughout the stages of the process of innovation. From the customers’ point of view, being involved in innovation processes and becoming a part of the organ-ization is a desire of an increasing number of them. Customers are demanding more individual and more tailored products. They are increasingly knowledgeable and capable of designing and produc-ing their own products and services. Due to the fact that their influence on product development is positively related to the quality of the new product (Sethi, 2000), more and more organizations appreciate them as innovation actors and are willing to pay them for their input. Today, customers are not only involved in the qualification of products (Callon, Méadel, & Rabeharisoa, 2002; Callon & Muniesa, 2005; Grabher, Ibert, & Flohr, 2009) but also allowed to customize and evaluate them on the path to innovation (Franke & Piller, 2004; Piller & Walcher, 2006; von Hippel & Katz, 2002; von Hippel, 2001). Moreover, there is an abundance of studies that stress the customers’ influence on effectiveness (de Luca & Atuahene-Gima, 2007; Kleinschmidt & Cooper, 1991; Kristensson, Matthing, & Johansson, 2008; Still, Huhtamäki, Isomursu, Lahti, & Koskela-Huotari, 2012) and risk (Bayer & Maier, 2006; Enkel, Kausch, & Gassmann, 2005; Enkel, Perez-Freije, & Gassmann, 2005). While the latter comprises the risk of customer integration as well as the customers’ influence on market risks, e.g., during new product development, studies on effectiveness are mostly concerned with customer-orientation and products/services in line with customers’ expectations (Atuahene-Gima, 1996, 2003; Fuchs & Schreier, 2011). The accompanying change in understanding became known as open innovation (OI; first coined by Chesbrough in 2003) and represents a paradigm shift, where organizations switch their focus from internally generated innovation (i.e., ideation, in-house R&D, etc.) toward external knowledge and open innovation processes, thus, allowing them to integrate external ideas and actors, i.e. custom-ers (Chesbrough, 2006) and other external stakeholders (Laursen & Salter, 2006). Since then, OI has been identified as a success factor for increasing customer satisfaction (Füller, Hutter, & Faullant, 2011; Greer & Lei, 2012) and growing revenues (Faems, De Visser, Andries, & van Looy, 2010; Mette, Moser, & Fridgen, 2013; Spithoven, Frantzen, & Clarysse, 2010). In addition to that, by open-ing their doors to external experts and knowledge workers (Kang & Kang, 2009), organizations cope with shorter innovation cycles, rising R&D costs, and the shortage of resources (Gassmann & Enkel, 2004). Parallel to the paradigm shift in innovation, another shift has taken place in information and com-munication technologies (Kietzmann, Hermkens, McCarthy, & Silvestre, 2011). Only a few years ago, when customer integration was still very costly, companies had to fly in customers, provide facilities onsite, permanently assign employees to such activities, and incentivise each task execut-ed by customers. Today, emerging technologies (subsumed under the term ‘social software’) help integrating customers or other external stakeholders, who are increasingly familiar with the such technologies from personal usage experience (Cook, 2008), and grant them access from all over the world in a 24/7 fashion. Examples include blogging tools, social networking systems, or wikis. These technologies help organizations to access customer knowledge, facilitate the collaboration with customers (Culnan, McHugh, & Zubillaga, 2010; Piller & Vossen, 2012) at reduced costs and allow them to address a much larger audience (Kaplan & Haenlein, 2010). On the other hand, customers can now express their needs in a more direct way to organizations. However, each technology or application category may present a completely different benefit to the process of innovation or parts of it and, thus, the innovation itself. Reflecting these developments, organizations need to know two things: how can they exploit the customers’ knowledge for innovation purposes and how may the implementation of social soft-ware support this. Hence, this research addresses the integration of customers in organizational innovation, i.e. new product development. It addresses how and why firms activate customers for innovation and which contribution customers provide to the process of innovation. Additionally, it investigates which tasks customers may take over in open innovations projects and which strategies organiza-tions may choose to do so. It also addresses which social software application supports each task best and how organizations may select the most suitable application out of a rapidly growing num-ber of alternatives. The nature of this research is recommendatory and aims at designing a solution for organizations that are interested in the potential contribution of customers during innovation, already involve customers in innovation tasks or plan to do so. Following the recommendations of this research should result in a more effective organizational exploitation of customer knowledge and their workforce and, thus, a value added to innovation and the outcomes of the process of innovation, e.g., a product that better fits the customers’ expectations and demands or consequently a better adoption of the product by the customer.

The possibilities that exist with today’s online environments are huge. Today more data than ever before is stored each day in different forms online, and it is steadily increasing. With increasing amounts of data in the online databases, the need for evaluation and optimization in information systems is ever increasing. The field studies within this project was done on demand by a recruitment agency located in Great Britain. The main area of this study was to investigate the user experience and workflow within an applicant tracking software (ATS). With the Task-Technology Fit (TTF) theory as theoretical framework, this study aimed to apply this theory in the evaluation of the ATS called Bullhorn, by evaluating the match between Task characteristic and Technology characteristic through qualitative methods. Results shows how user experience and performance is affected by the current TTF construct. / Möjligheterna i dagens onlinevärld är oändliga. Idag samlas det varje dag in mer data än någonsin innan i olika former online, och detta fortsätter att öka stadigt. Med ökande mängder data i databaserna online, ökar behovet av utvärdering och optimering inom informationssystem. Fältstudierna som genomfördes i detta projekt gjordes på beställning av ett rekryteringsbolag i Storbritannien. Huvudområdet för detta projekt var att undersöka användarupplevelsen och arbetsflödet i en söktjänst för arbetssökande. Med Task-Technology Fit-teorin (TTF) som teoretiskt ramverk var målet med denna studie att applicera denna teori i utvärderingen av söktjänsten Bullhorn, genom att utvärdera matchningen mellan uppgifterna som användarna behöver genomföra och tjänstens tekniska möjligheter via kvalitativa metoder. Resultatet visar hur användarupplevelsen och användarens prestation påverkas av den nuvarande TTF-matchningen.

Involving customers in the creation and design process of new products and services has been dis-cussed in practice and research since the early 1980’s. As one of the first researchers, von Hippel (1986) shed light on the concept of Lead Users, a group of users who are able to provide most accu-rate data on future needs for organizations. Subsequently, many scholars emphasized different areas of contribution for customers and how they provide assistance to the process of innovation. First of all, customers may contribute to product innovation (Cooper & Kleinschmidt, 1987; Driessen & Hillebrand, 2013; Füller & Matzler, 2007; Gruner & Homburg, 2000; Sawhney, Verona, & Prandelli, 2005; Snow, Fjeldstad, Lettl, & Miles, 2011; Yang & Rui, 2009) and service innovation (Abecassis-Moedas, Ben Mahmoud-Jouini, Dell’Era, Manceau, & Verganti, 2012; Alam, 2002; Chesbrough, 2011; Larbig-Wüst, 2010; Magnusson, 2003; Paton & Mclaughlin, 2008; Shang, Lin, & Wu, 2009; Silpakit & Fisk, 1985), e.g., by co-creating values (Prahalad & Ramaswamy, 2004), such as concepts or designs as well as reviewing and testing them throughout the stages of the process of innovation. From the customers’ point of view, being involved in innovation processes and becoming a part of the organ-ization is a desire of an increasing number of them. Customers are demanding more individual and more tailored products. They are increasingly knowledgeable and capable of designing and produc-ing their own products and services. Due to the fact that their influence on product development is positively related to the quality of the new product (Sethi, 2000), more and more organizations appreciate them as innovation actors and are willing to pay them for their input. Today, customers are not only involved in the qualification of products (Callon, Méadel, & Rabeharisoa, 2002; Callon & Muniesa, 2005; Grabher, Ibert, & Flohr, 2009) but also allowed to customize and evaluate them on the path to innovation (Franke & Piller, 2004; Piller & Walcher, 2006; von Hippel & Katz, 2002; von Hippel, 2001). Moreover, there is an abundance of studies that stress the customers’ influence on effectiveness (de Luca & Atuahene-Gima, 2007; Kleinschmidt & Cooper, 1991; Kristensson, Matthing, & Johansson, 2008; Still, Huhtamäki, Isomursu, Lahti, & Koskela-Huotari, 2012) and risk (Bayer & Maier, 2006; Enkel, Kausch, & Gassmann, 2005; Enkel, Perez-Freije, & Gassmann, 2005). While the latter comprises the risk of customer integration as well as the customers’ influence on market risks, e.g., during new product development, studies on effectiveness are mostly concerned with customer-orientation and products/services in line with customers’ expectations (Atuahene-Gima, 1996, 2003; Fuchs & Schreier, 2011). The accompanying change in understanding became known as open innovation (OI; first coined by Chesbrough in 2003) and represents a paradigm shift, where organizations switch their focus from internally generated innovation (i.e., ideation, in-house R&D, etc.) toward external knowledge and open innovation processes, thus, allowing them to integrate external ideas and actors, i.e. custom-ers (Chesbrough, 2006) and other external stakeholders (Laursen & Salter, 2006). Since then, OI has been identified as a success factor for increasing customer satisfaction (Füller, Hutter, & Faullant, 2011; Greer & Lei, 2012) and growing revenues (Faems, De Visser, Andries, & van Looy, 2010; Mette, Moser, & Fridgen, 2013; Spithoven, Frantzen, & Clarysse, 2010). In addition to that, by open-ing their doors to external experts and knowledge workers (Kang & Kang, 2009), organizations cope with shorter innovation cycles, rising R&D costs, and the shortage of resources (Gassmann & Enkel, 2004). Parallel to the paradigm shift in innovation, another shift has taken place in information and com-munication technologies (Kietzmann, Hermkens, McCarthy, & Silvestre, 2011). Only a few years ago, when customer integration was still very costly, companies had to fly in customers, provide facilities onsite, permanently assign employees to such activities, and incentivise each task execut-ed by customers. Today, emerging technologies (subsumed under the term ‘social software’) help integrating customers or other external stakeholders, who are increasingly familiar with the such technologies from personal usage experience (Cook, 2008), and grant them access from all over the world in a 24/7 fashion. Examples include blogging tools, social networking systems, or wikis. These technologies help organizations to access customer knowledge, facilitate the collaboration with customers (Culnan, McHugh, & Zubillaga, 2010; Piller & Vossen, 2012) at reduced costs and allow them to address a much larger audience (Kaplan & Haenlein, 2010). On the other hand, customers can now express their needs in a more direct way to organizations. However, each technology or application category may present a completely different benefit to the process of innovation or parts of it and, thus, the innovation itself. Reflecting these developments, organizations need to know two things: how can they exploit the customers’ knowledge for innovation purposes and how may the implementation of social soft-ware support this. Hence, this research addresses the integration of customers in organizational innovation, i.e. new product development. It addresses how and why firms activate customers for innovation and which contribution customers provide to the process of innovation. Additionally, it investigates which tasks customers may take over in open innovations projects and which strategies organiza-tions may choose to do so. It also addresses which social software application supports each task best and how organizations may select the most suitable application out of a rapidly growing num-ber of alternatives. The nature of this research is recommendatory and aims at designing a solution for organizations that are interested in the potential contribution of customers during innovation, already involve customers in innovation tasks or plan to do so. Following the recommendations of this research should result in a more effective organizational exploitation of customer knowledge and their workforce and, thus, a value added to innovation and the outcomes of the process of innovation, e.g., a product that better fits the customers’ expectations and demands or consequently a better adoption of the product by the customer.:1 Introduction 2 Theoretical foundation 3 Research areas and focal points 4 Research aims and questions 5 Methods 6 Findings 7 Conclusion References Essay 1: The Role of External Knowledge in Open Innovation – A Systematic Review of Literature Essay 2: External Knowledge in Organisational Innovation – Toward an Integration Concept Essay 3: Idea Mining – Text Mining Supported Knowledge Management for Innovation Purposes Essay 4: How do Tasks and Technology fit? – Bringing Order to the Open Innovation Chaos

Contexte : Les premières implantations PACS (Picture Archiving and Communication System) remontent aux années 80. Le rehaussement récent du PACS au sein d’un centre hospitalier universitaire a permis d’étudier l’introduction d’innovations dans une technologie mature. Objectif : Dans un premier temps, effectuer une revue de la littérature sur les études évaluant la perceptions des utilisateurs de l’implantation des PACS. Deuxièmement, évaluer dans une étude de cas si le niveau d’alignement entre les tâches et la technologie prédit l’utilisation et la perception des bénéfices. Méthodes : Il y a eu une revue systématique de la littérature afin d’identifier les études sur la perception des utilisateurs du PACS. Une adaptation du modèle TTF (Task-Technology-Fit) développé par Goodhue (1995) a servi de base théorique pour l’étude de cas effectuée par questionnaire auto-administré. Résultats : Les modèles recensés dans la revue systématique sont mieux adaptés à des nouvelles implantions PACS qu’à des systèmes matures en évolution. Il y a une corrélation significative entre le niveau de l’alignement, tel que perçu par les utilisateurs, et la perception des bénéfices nets, ainsi que l’utilisation de la technologie. L’étude a démontré un écart entre la perception des utilisateurs et celle des développeurs interviewés. Conclusions : Cette étude supporte la validité du concept alignement tâche-technologie dans l’analyse d’un rehaussement PACS. Il est important de maintenir une interaction soutenue entre développeurs et utilisateurs, qui va audelà de la phase initiale de développement. / Context: The first PACS deployments date to the early 1980’s. The recent upgrade of PACS in a university teaching hospital has offered the opportunity to study the introduction of innovations in a mature technology. Objective: First, to conduct a literature review of studies evaluating user perceptions following deployment of PACS. Second, to evaluate in a case study if task-technology fit predicts utilisation and perceived benefits. Methods: A systematic review of the literature was conducted to identify studies evaluating user perceptions. An adaptation of the Task-Technology-Fit model developed by Goodhue (1995) served as a theoretical basis for the case study conducted with an auto-administered survey. Results: The models used in the studies identified in the review are more suited for initial deployments of PACS, rather than mature systems in a state of continuous evolution. There is a significant correlation between the level of task-technology fit and the users’ perception of net benefits, as well as use. The study also revealed a divide between the perception of users and that of developers involved in product evolution. Conclusion: The findings validate the use of task-technology fit to study a PACS upgrade. It is important to maintain a continuous interaction between users and developers beyond the early phases of product development.

Contexte : Les premières implantations PACS (Picture Archiving and Communication System) remontent aux années 80. Le rehaussement récent du PACS au sein d’un centre hospitalier universitaire a permis d’étudier l’introduction d’innovations dans une technologie mature. Objectif : Dans un premier temps, effectuer une revue de la littérature sur les études évaluant la perceptions des utilisateurs de l’implantation des PACS. Deuxièmement, évaluer dans une étude de cas si le niveau d’alignement entre les tâches et la technologie prédit l’utilisation et la perception des bénéfices. Méthodes : Il y a eu une revue systématique de la littérature afin d’identifier les études sur la perception des utilisateurs du PACS. Une adaptation du modèle TTF (Task-Technology-Fit) développé par Goodhue (1995) a servi de base théorique pour l’étude de cas effectuée par questionnaire auto-administré. Résultats : Les modèles recensés dans la revue systématique sont mieux adaptés à des nouvelles implantions PACS qu’à des systèmes matures en évolution. Il y a une corrélation significative entre le niveau de l’alignement, tel que perçu par les utilisateurs, et la perception des bénéfices nets, ainsi que l’utilisation de la technologie. L’étude a démontré un écart entre la perception des utilisateurs et celle des développeurs interviewés. Conclusions : Cette étude supporte la validité du concept alignement tâche-technologie dans l’analyse d’un rehaussement PACS. Il est important de maintenir une interaction soutenue entre développeurs et utilisateurs, qui va audelà de la phase initiale de développement. / Context: The first PACS deployments date to the early 1980’s. The recent upgrade of PACS in a university teaching hospital has offered the opportunity to study the introduction of innovations in a mature technology. Objective: First, to conduct a literature review of studies evaluating user perceptions following deployment of PACS. Second, to evaluate in a case study if task-technology fit predicts utilisation and perceived benefits. Methods: A systematic review of the literature was conducted to identify studies evaluating user perceptions. An adaptation of the Task-Technology-Fit model developed by Goodhue (1995) served as a theoretical basis for the case study conducted with an auto-administered survey. Results: The models used in the studies identified in the review are more suited for initial deployments of PACS, rather than mature systems in a state of continuous evolution. There is a significant correlation between the level of task-technology fit and the users’ perception of net benefits, as well as use. The study also revealed a divide between the perception of users and that of developers involved in product evolution. Conclusion: The findings validate the use of task-technology fit to study a PACS upgrade. It is important to maintain a continuous interaction between users and developers beyond the early phases of product development.