The Internet of Things is increasingly becoming an essential factor for organisational success. This study focuses on a micro level perspective how sensor-based IoT systems address process information requirements in organisations. The study encompasses three different cases were IoT-based systems were implemented and what the automational, informational and transformational effects have been on their processes. To gauge these effects, we have used a framework for assessing the business value of the IoT implementations. Moreover, we have used a framework for generating digital options to address the information requirements in processes. The purpose of the study is to measure the effects on business processes, how actors explore innovation opportunities enabled by IoT and how sensor-based system address information requirements. The results of the study identified several complex factors and contribute with practices on how to utilise sensor-systems as an enabling technology for continued process innovation.

Aus der Einführung: "Die Informationstechnik ist seit den Anfängen von CAD vor ca. 50 Jahren ein wesentlicher Impulsgeber für die Produktentwicklung und hat maßgeblichen Anteil an Prozessinnovationen wie dem Global Engineering oder der Digitalen Fabrik. Längst geht es aber heute nicht mehr allein um die Geometriebeschreibung zukünftiger Produkte, sondern um die möglichst umfassende Begleitung und Ergänzung des realen Produkts durch das virtuelle Produkt: von der ersten Idee bis zum Recycling. Die umfassende Vision des virtuellen Produkts als Pendant zum realen Produkt (Spur & Krause 1997) ist untrennbar mit dem Fortschritt der Informationstechnologie verbunden."

Titel: Den ofrivilligt digitala ledaren – en studie om den av Covid-19 pandemin påtvingade digitala omställning av ledarskap och styrning i kommunikations- och informationsväxling Nivå: Kandidatuppsats i företagsekonomi (Examensarbete på grundnivå) Författare: Mats Andersson & Marcus Bjuhr Handledare: Akmal Hyder Examinator: Aihie Osarenkhoe Datum: 2022-05-25   Syfte: Syftet är att undersöka och förstå hur Covid-19 pandemin påverkat ledarskapets digitala omställning i svenska företag samt att förklara hur verksamheterna hanterat den snabba förändringen av kommunikations- och informationskanaler. Metod: Denna studie använder en kvalitativ metod med en hermeneutisk kunskapssyn vilken erkänner komplexiteten i sociala strukturer och tolkar möjliga sanningar genom verkligheten. Vidare används en flerfallsstudie för att undersöka hur ledarskap och styrning förändrats, detta genom att intervjua chefer med personalansvar via semi-strukturerad intervjumetod. Resultat & Slutsats: De resultat som studien påvisar menar att den problematik som den påtvingade omställningen inneburit har varit mindre än förväntad och snarare inneburit förbättringspotentialer genom den ökade användningen av digitala verktyg. Detta relateras till den rapport som EU-kommissionen presenterat kring Sveriges högpresterande och digitala utveckling som land samt det ökade informationsflöde som detta möjliggjort. Examensarbetets bidrag: Arbetets bidrag till den aggregerade kunskapen relateras främst till att stödja VUCA-teorin som avser ökad komplexitet kring ledarskap i en volatil omvärld. Ett andra bidrag är att ge stödjande argument till att satsa på ökad digital infrastruktur verkar positivt för konkurrenskraft i relation till digitaliseringen samt den anpassningsbarhet som moderna ledare och organisationer behöver enligt aktuell forskning. Förslag till fortsatt forskning: Denna studies förslag till framtida forskning är att undersöka andra länder, särskilt sådana som har en lägre digital mognad enligt EU-kommissionens bedömningsmatris (Digitaliseringsrådet, 2022).  Nyckelord: Business process management, Covid-19, Digitalization, Digital economy, Process innovation, Leadership, Manager / Title: The involuntary digital leader – a study on the Covid-19 pandemic´s forced digital transformation of leadership and organization in communication and information exchange  Level: Bachelor’s degree in business administration (student thesis) Authors: Mats Andersson & Marcus Bjuhr Supervisor: Akmal Hyder Examiner: Aihie Osarenkhoe Date: 2022-05-25   Aim: The purpose of the thesis is to investigate and understand how the Covid-19 pandemic has affected the leadership digital transformation in Swedish businesses and explain how the organizations managed the rapid change of communication and information channels. Method: The thesis applies a qualitative method with a hermeneutic view of knowledge in which identifies the complexity of social structures and interpret the potential truths. The method also implements a multi-case study to examine the leadership and organizational change by interviewing managers with personnel responsibilities with a semi-structured method. Results and conclusions: The results this thesis presents point towards smaller problems with the forced digital transformations than expected. It also tends towards improvement potentials due to the increased usage of digital tools. This can be linked to the report that the EU-commission revealed where Sweden is a high-performance country with a high level of digital maturity. Contribution of the thesis: The contribution this thesis offers to the aggregated knowledge relates foremost towards the VUCA-theory which explain the complexity of leadership in a volatile world. A second contribution is the supportive claim of investing in a country’s digital infrastructure which affects the competitiveness in relation top the digitalization and the adaptability of modern leaders and organizations. Keywords: Business process management, Covid-19, Digitalization, Digital economy, Process innovation, Leadership, Manager

The literature emphasises the need to integrate innovation initiatives under the umbrella of the total quality management (TQM) philosophy. Such integration is instrumental towards achieving and sustaining a superior organisational performance. Using a sample of 229 Portuguese manufacturing organisations, factor and regression analyses procedures were used to assess the impact on organisational performance of innovation for small and large organisations in the Portuguese TQM business context. The results of this study point to the significance of the size of the organisation, and product and process innovations for organisational performance. Organisational innovation was not found to have a significant impact on organisational performance. These results might be attributed to specific ownership, which is associated with process and product innovation. Based on the results of this study, it is concluded that small organisations might want to consider directing their innovation investments towards management aspects such as processes and products. In this context, top-down organisational innovation might take more time and effort.

Purpose: The study primarily aims to examine the effect of internal innovation in determining the firm performance for the textile industry of Pakistan by testing the research framework of innovation diffusion theory. Additionally, the study also explores the moderating role of collaborative innovation in explaining the relationship between internal innovation and a firm’s performance in the target population. Methodology: The study used a self-administrative questionnaire-based survey technique to collect data from the participants. Due to the prevailing Covid-19 pandemic situation globally, the data was collected online using the Convenience sampling approach. The outcome variable of the study was firm performance, while the explanatory variable is internal innovation, which is measured by product and process innovation. Additionally, collaborative innovation was used as the moderating variable of the study. The population of the study was the textile sector of Pakistan. The unit of analysis was managerial employees (at all levels) working in the textile industry of Pakistan. The online questionnaire was shared with approximately, 100 target people successfully and completely provided their unbiased responses using online means. The researchers analyzed the collected data using SPSS software. The analysis techniques include descriptive statistics, correlation, reliability analysis (using Cronbach alpha), convergent reliability & validity (using outer loadings, composite reliability, and average variance extracted), VIF, and regression for testing the hypotheses. Findings: The study found that product innovation and process innovation both serve as critical drivers for the firm performance in the textile industry of Pakistan. Moreover, collaborative innovation plays a complementary role as the significant moderator between the internal innovation process and the firm’s performance in the target population. The results concluded the acceptance and support of the required hypothesis of the study, including the acceptance of innovation diffusion theory for the textile industry of Pakistan, and finally the consistency of results with existing literature. Implications:  Contribution of Study: Existing literature lacks to provide the mechanism and understanding that how internal innovation (product innovation and process innovation) collaborative innovation shapes the effective and efficient performance of the firms in the textile industry of Pakistan. Therefore, the lack of research work and clarity in the existing literature makes this study meaningful. Moreover, the contributions of the study are multifaceted as the first time this study is being conducted in an emerging economy Pakistan. Novelty: The findings of the study add the literature for the domain of innovation and performance, especially, in the case of the textile sector of Pakistan with the partially moderating impact of collaborative innovation. The study also contributes towards the acceptance of innovation diffusion theory in the textile industry of Pakistan. Limitations & Recommendations: The findings of the study apply to the Textile sector only due to the specific nature of their operations. The prospective researchers in this domain can consider further dimensions of innovations to examine their impact on a firm’s performance. Additionally, innovation performance can also be considered for future studies. Furthermore, cross-sector analysis can be performed for understanding how innovation works in different sectors.

Background: In today's digital world, there is increasing importance on cross-platform performance testing and the challenges faced by businesses in achieving efficient performance for applications across multiple platforms. Predictive models, such as machine learning and regression, have emerged as potential solutions to predict performance to be quickly analyzed, thus eliminating the need to execute an entire environment. Predicting performance can help firms save time and resources to keep pace with market demand, but potential risks and limitations need to be considered. With the increasing availability of data, predictive models have become effective problem-solving methods in various industries, including the testing industry. Objectives: This research aims to investigate the economic consequences and opportunities of implementing predictive models to predict cross-platform performance for firms operating in the software market and evaluate the performance of three models when predicting cross-platform performance. The study aims to add arguments to help businesses make informed decisions on the adoption of predictive models. Methods: The methodology employed in this research involved evaluating Multiple Linear Regression, Multiple Neural Network, and Random Forest, to gain insight into how such models perform when predicting performance. In addition to this analysis, interviews were conducted with industry experts to get an understanding of current processes and the potential benefits of adopting predictive models to identify the economic consequences of implementing such models. Results: The result shows that Multiple Linear Regression was the most promising one, with an R2 value of 0.79. Additionally, the research revealed that the current testing process faces difficulties when testing on multiple platforms. While predicting performance can provide cost and time savings, challenges and risks, such as data privacy and model trust, must also be considered. Conclusions: Multiple Linear Regression exhibited the most favorable performance among the evaluated models, with consistent results across all test runs and indicating a linear relationship. The economic consequences identified were the continuously required maintenance and updates of predictive models to remain accurate throughout the lifecycle. This implies ongoing costs, such as the complexity and cost of generating and storing the necessary data to train the models. Thus, the adoption of predictive models is still in its early stages, and while there are significant benefits, there are also challenges to address.

As healthcare costs are rising globally and biologic treatments are a growing segment of the cost, governments have created biosimilar regulatory pathways in attempt to lower the costs of biologics. Biosimilars may be viewed as a “pure” or distinct type of process innovation completely separate from product innovation due to the Regulatory requirements and this novel phenomenon allows, perhaps for the first time, process innovation to be studied independently from product innovation. This phenomenon is researched using the competitive dynamic Awareness-Motivation-Capability (AMC) model structure. Since biosimilars are still relatively new, the impact of the biosimilars from a practical and academic viewpoint is emerging and in particular within the US market. This research creates a biosimilar model and metrics, filling a current gap in the literature, and quantitatively evaluates the actions that firms face regarding entering into the biosimilars market due to key metrics such as patent / portfolio risk, prior biologics or generic experience, strength of the R&D pipeline, and the firm’s R&D intensity. The biosimilar construct due to the strict regulatory pathway definition provides this unique and novel opportunity to study process innovation and the impact on competitive dynamics without the interference of product innovation. This research is anticipated to contribute to the practical and academic understanding of process innovation via the biosimilar phenomenon and the competitive dynamics of market entry as well as to promote further managerial research into this area of biosimilars. / Business Administration/Strategic Management

Den tekniska utvecklingen har möjliggjort ett mer uppkopplat samhälle genom enklare informationstillgång och mer avancerad informationshantering. Den här framfarten har legat till grund för utveckling av samlingsbegreppet Internet of Things, där automatiserade datainsamlingssystem är betydande för insamling av mer kvantitativa datamängder. Detta har lett till att företag inom flera olika industrier har integrerat tekniken i delar av verksamheten för att samla in en betydande datamängd i syfte att utveckla och förbättra de egna processerna. Intresset och framförallt behovet av den här typen av teknologi finns inom byggindustrin. För ett byggföretag som vill arbeta med digitala lösningar i deras arbete gäller att skapa förståelse för varför den typen av lösning ska användas och hur den kan nyttjas på bästa sätt. Vid implementering och anpassning av en ny teknik är det nödvändigt för företag att identifiera vilka möjligheter och hinder som kan uppstå. Därav är syftet med studien att undersöka möjligheten att samla in realtidsdata genom en automatiserad insamlingsprocess i produktionsfasen hos ett byggföretag. Vidare undersöks hur processen bidrar till kvalitetssäkring och ständiga förbättringar i byggprojekten. Detta för att skapa medvetenhet hos byggföretag om en ny teknik som kan underlätta deras arbete och hindra uppkomst av problem. En fallstudie har genomförts hos byggföretaget JM AB som har en lång erfarenhet av byggprocesser och byggprojekt. För att skapa förståelse kring studiens ämne och slutsatser har en en teoretisk referensram innehållandes teorier om bland annat kvalitetssäkring och datainsamling byggts upp. Genom tio intervjuer med anställda av olika befattningar, två observationer på ett av fallföretagets byggprojekt och en intervju med ett externt företag sammanställdes en empirisk undersökning. På så sätt erhölls insikt i hur fallföretaget arbetar med datainsamlingsprocesser och vilka tekniker som finns på marknaden. Genom analys av fallstudien framkom det tydligt att fallföretaget inte har välutarbetade datainsamlingsprocesser inom flera områden i byggproduktionen. En viktig slutsats i studien är att användandet av ett processinnovationsramverk kan skapa förutsättningar för en effektiv och automatiserad datainsamlingsprocess. Ramverket ger stöd till huruvida en automatisk datainsamlingsprocess är lönsamt samt skapar förståelse kring processen innan den är redo att implementeras. Dessutom möjliggör en automatiserad datainsamlingsprocess kvalitetsförbättringar med hjälp av ett kvalitetskontrollramverk som kan öka kvaliteten genom att reducera problem och lösa dem fortare. Kvalitetskontrollerna blir systematiska och utifrån genererad data kan jämförelser göras för att identifiera defekter så att arbete mot snabbare handlingsåtgärder kan skapas. Utifrån slutsatserna har fyra rekommendationer tagits fram, den första är att använda processinnovationsramverk vid undersökning av en ny automateringsprocess. Den andra är att testa automatiserade datainsamlingsprocesser i mindre projekt för att erhålla ökad förståelse. Den tredje är att systematiskt arbeta med ett kvalitetskontrollramverk utifrån genererad data. Den sista rekommendationen är att använda insamlad data till faktabaserade beslut och sträva mot ständiga förbättringar. / Technological developments have enabled a more connected society with easier access to information that creates opportunities for more advanced information management. This has been the basis for development of the generic term Internet of Things, where automated data collection systems are significant for the collection of quantitative data set. Companies in various industries are embracing the integration of this type of technology in their businesses to generate data that is possessed to improve their processes. The interest and especially the need for this type of technology is huge in the construction industry.   For construction companies that wants to work with digital solutions, it is important to create an understanding of why this type of solution is to be used and how it best can be utilized. In implementation and adaption of a new technology, it is necessary for companies to identify the opportunities and obstacles that may arise. Hence, the purpose of this study is to examine the feasibility of collecting real-time data through an automated collection process in the production phase at a construction company, and how it contributes to quality assurance and continuous improvement in construction projects. In this way, awareness among construction companies of a new technique can facilitate their work and prevent upcoming problems. A case study has been carried out at the construction company JM AB who has a long experience of construction processes. To create an understanding about the study topic and conclusions, a theoretical framework was compiled including theories about quality assurance and data collection. Through ten interviews with employees of different positions, two observations at one of the case company’s construction projects and one interview with an external company, an empirical study was compiled. In this way, insights were obtained into how the case company is working with data collection processes and what techniques that are available on the market. Through analysis of the case study, it crearly appeared that the case company does not have well-developed data collection processes in several areas of the building production. One important conclusion of the study is that the use of a process innovation framework can create conditions for an efficient and automated data collection process. The framework supports whether an automated data collection process is profitable and it creates an understanding of the process prior of its implementation. Another important conclusion is that an automated data collection process allows quality improvements through the help of a quality control framework that can increase the quality by reducing problems and solving them faster. Hence, quality controls become systematic and based on generated data, comparisons can be made to identify defects in order to work systematically toward faster action measures. Based on the findings, four recommendations were developed. The first one is to use process innovation framework for the examination of a new automatic process. The second is to test automated data collection processes into smaller projects to obtain greater understanding. The third is to work systematically on a quality control framework based on generated data. The last recommendation is to use the collected data for fact-based decisions and to strive for continuous improvement.

Problem/Purpose: Process prioritisation is an ill-structured and complex problem that remains a mystery phase in business process management (BPM) research. More explorative approaches are called upon to tackle process management problems, to facilitate process innovation and to design new processes in dynamic environments. This dissertation aims (i) to design and evaluate a Prioritisation and Categorisation Method (PCM) for addressing process prioritisation problems; and (ii) to explore process innovation by disruptive technologies. Research methods: This research follows the design science research (DSR) paradigm. The design exploration and the engaged scholarship approaches are also adapted. The demonstration and evaluation of the Prioritisation and Categorisation Method have been conducted with case studies in large Swedish companies, i.e. Seco Tools and Ericsson. An empirical study of the impacts of disruptive technologies on process innovation was conducted at a large insurance company in Sweden. Results: This research has led to the design and evaluation of the PCM: a new context-aware, effective and holistic method for BPM. In addition, the lessons learnt from the insurance case deepened the understanding of the challenges that are faced by a company when exploring new capabilities (e.g. processes and IT) for future business. Such lessons also emphasise the necessity of configuring PCM based upon business contingencies and industry factors in process prioritisation. Contributions: This dissertation contributes a novel method to explore BPM in a holistic, yet flexible and effective way. The challenges identified in process innovations improve the configuration capabilities of the PCM through a deeper understanding of the dynamic capabilities within organisations (Capability Layer Model-CLM). This research contributes design knowledge to DSR in the forms of the PCM as an invention, and the three design principles for the PCM: design by holistics, design by commitments and design by explorations. The research is evaluated as good BPM and good design science research.

The aim of the thesis is to assess the effectiveness of innovation and evaluate its economic impact on the company. Theoretical part contains topics regarding innovations and also potential ways of assessing effectiveness and impact of innovation. Practical part presents fundamental information about the company and its current economic situation. Once all basic information is presented, innovation is described in detail followed up by evaluation of its effectiveness and impact on the company.