The aim of our research paper is to depict and analyze the new trends and changes happening in the Information Technology industry during the recent years, that are most likely to have a long-lasting impact on how the usage of software technology is evolving. The overall trend that we are noticing in this market is about shifting more and more software applications from local computers to online networks generally known as The Cloud (the concept itself is named Cloud Computing). The reason for choosing this topic is that, overall, the Information Technology industry is deeply involved in our everyday lives. Therefore, it is important for us as individuals or businesses to be aware of the new trends happening in this field and learn how we can benefit from them. We will research these trends from the perspective of the providers of Cloud Computing services. We will analyze the challenges of establishing a new market for these services and debate the pros and cons of being the first mover or follower among big and small players. We will also investigate whether there is a dominant design under development. As means for our analysis, we will research the three main technologies used as a mean to implement the new concept of Cloud Computing, which are Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). One result of our study is that the main players on the Cloud Computing market do not think in terms of national markets or geographical borders about their products. Since they are providing online services, we conclude that it is normal for all the players to see the market as one single entity rather than limiting themselves to geographical areas, which are obviously irrelevant for the Internet market. Another result is that there is confusion among the players when it comes to defining Cloud Computing, Software as a Service and Platform as a Service and the difference between these concepts. We consider as the main reasons for this confusion the fact that the Cloud Computing industry is not yet standardized, and every firm is having its own way of dealing with these new concepts. However, we believe that there is a complex market system under way. All the firms are apparently waiting for a technological standardization or a dominant design, before they will fully adopt and implement this technology. Moreover, most companies we analyzed believe that Cloud Computing will be, one way or another, the future in the Information Technology and Communication industry.

Teknologiska framsteg inom webbteknologier, virtualisering samt ökad bandbredd har gett upphov till cloud computing, en disruptiv innovation som leder till tjänstefiering av IT-industrin där produkter som hårdvaror och mjukvaror omvandlas till tjänster och som görs tillgängliga för kunder via Internet. Software-as-a-service är en del av cloud computing och avser applikationer som är installerade och körs på en molninfrastruktur och som tillgängliggörs som en tjänst för kunder via en webbläsare eller ett tunt klientgränssnitt. Att leverera mjukvara som en tjänst är en trend som under de senaste åren har vuxit och som förväntas fortsätta växa och som har inneburit att nya intäktsströmmar för mjukvara har möjliggjorts.    Tidigare studier har visat att det finns flera olika intäktsströmmar för software-as-a-service som kan fungera hållbart och att valet bör ske genom att ta hänsyn till en mängd olika variabler. Många av studierna inom området är dock konceptuella och bygger inte på primärdata. Dessutom är de flesta studier äldre än fyra år. Vidare finns det enligt vår vetskap inte några studier som undersöker hur affärsmodellen som helhet påverkas av valet av intäktsströmmar för software-as-a-service.     Studien har syftat till att skapa förståelse för vad som påverkar mjukvaruföretags val av intäktsströmmar. Detta har betraktats utifrån ett affärsmodellsperspektiv med hjälp av verktyget Business Model Canvas.   En kvalitativ små-N-studie har genomförts. Empiri har samlats in genom att utföra fem intervjuer med olika företag inom mjukvarubranschen som levererar mjukvara enligt software-as-a-service. En kvalitativ innehållsanalys i kombination med ramverket Business Model Canvas har använts för att analysera insamlad empiri. Studien resulterade i ett flertal faktorer som påverkar företags val av intäktsströmmar. Dessa är:  Mjukvarans komplexitet, varumärket, behov av återkommande intäkter, leverans, kundernas inflytande, förväntat användarmönster, marknadsacceptanssamtlagar och regleringar.Vissa av de identifierade faktorerna bekräftar upptäckter som gjorts i tidigare forskning medan andra faktorer, utifrån vår kännedom, tillför ny kunskap inom området. Analysen av de identifierade faktorernas inverkan på affärsmodellen med hjälp av Business Model Canvas visade att det fanns en komplex koppling mellan faktorerna och affärsmodellens byggstenar. Varje identifierad faktor kan ha en direkt inverkan på en eller flera byggstenar i affärsmodellen. Detta tyder på att valet av intäktsströmmar för mjukvara är en komplicerad process och att valet bör baseras utifrån affärsmodellens övriga byggstenar. / Technological advances in web technologies, virtualization and increased bandwidth have given rise to cloud computing, a disruptive innovation that has led to the servitization of the IT-industry where products such as hardware and software have transformed to services which are made available to customers through the internet. Software-as-a-service is a part of cloud computing and refers to applications that are installed and executed on cloud infrastructure and made available as a service to the customers through a web browser or thin client interface. Delivering software-as-a-service has been an increasing trend that is predicted to continue to grow. It has enabled new revenue streams for software.    Previous studies have shown that an array of revenue streams can work sustainably, but when choosing revenue streams, there are many variables to consider. This thesis examines aspects of these implications which have not been fully covered empirically and in recent years. Moreover, we examine how the business model is affected as a whole in the choice of revenue streams for software-as-a-service, an aspect which has been overlooked in the literature.    The purpose of the study has been to create an understanding of what affects the software companies’ choice of revenue streams. This has been viewed from a business model perspective through the Business Model Canvas framework.   A qualitative small-N-study has been undertaken. The empirical data were collected by five interviews at five different companies in the software industry who deliver their software according to the software-as-a-service model. A qualitative content analysis in combination with the Business Model Canvas framework has been applied to analyze the empirical data.   The outcome of the study resulted in identification of several factors which affected the companies choice in revenue streams These factors are: The complexity of the software, the need for recurring revenues, delivery, the customers’ influence, expected usage patterns, market acceptance and rules and regulations.Some of the factors have confirmed findings from previous studies while other factors according to our awareness have contributed to new knowledge in the field. The analysis of the identified factors on the business model by the Business Model Canvas has shown that there is a complex connection between the factors and the building blocks of the business model. This suggests that the choice of revenue streams for software is a complex process and should be grounded in the business model as a whole.

Emerging technologies are reshaping the digital landscape and competitive environment of highly technological companies with the introduction of artificial intelligence (AI). Firms are reacting by implementing digital transformation (DT) strategies aligning the organizational and technological factors towards leveraging AI-generated information. This thesis sheds new light on the topics of knowledge management (KM), DT, and AI in organizational practices with an emphasis on AI-enhanced software-as-a-service (SaaS). The research results in a conceptual framework, designed from the literature on AI, DT, KM, and dynamic capability view (DCV) uncovering three overarching concepts (internal capabilities, absorptive capacity, and technological competitiveness). This conceptual framework was then complemented by empirical data featuring primary data gathered from a single case study and secondary data from an internet-mediated data collection. The interviews in the case study were focused on managers with extensive experience in the semiconductor industry and operators working with the AI-enhanced SaaS tool. The analysis concludes in an updated conceptual framework, highlighting the interplay of a firm’s internal capabilities and an AI-enhanced absorptive capacity indicating three pathways toward achieving technological competitiveness in a highly technological environment. Additionally, a proposed solution is presented featuring an AI-enhanced tool operator as a new role, responsible for supporting organization-wide activities with AI-generated information.

Managing innovations is a well studied success factor for companies and organizations. This research focuses on the recently established Lean Startup Methodology (LSM) and the obstacles of implementing it in early- and later-stage business-to-business (B2B) Software as as Service (SaaS) startups. The scarcity of academic research around this framework, in contrast to its popularity, motivated the researchers’ aim to provide a better understanding on how it could be adapted to better fit the needs of these companies.Following an interpretivist paradigm, this qualitative research uses a literature review and semi-structured interviews for its purposes. Interviews were conducted with six individuals at four different early- and late-stage startups. The focus was on understanding the realities of working with innovation management and the different approaches at early and later stage startups. Startups face an abundance of ideas regarding what to do next, a hypothesis confirmed with this study. It is the researchers’ belief that the LSM does not provide sufficient tools for organizations to make an idea selection decision without committing too many resources initially. Lastly, the importance of product ownership for an effective innovation management process was validated.In conclusion, we present the need for an updated Lean Startup Methodology with a dedicated selection step to validate an idea early in the process. This contributes to the theory of innovation management and its practical implementation. The identified gap in academic research around frameworks tailored towards these types of organizations provides a good starting point for future research.

<p dir="ltr">In traditional Software as a Service (SaaS) enterprise applications, there is a need for easy-to-do machine learning (ML) frameworks. Additionally, SaaS applications are closely related when they form an application suite, which brings forth the need for an ML framework that can facilitate the “lift and shift” of ML model code in similar needs in multiple enterprise applications in a suite. To add to this, some SaaS applications are still using legacy infrastructure (on-premise) mandating the need for an ML framework that is backward compatible with coexisting platforms, both cloud and legacy on-premise infrastructure. This study first demonstrated that in SaaS applications, microservices were important ingredients to deploying machine learning (ML) models successfully. In general, microservices can result in efficiencies in software service design, development, and delivery. As they become ubiquitous in the redesign of monolithic software, with the addition of machine learning, the traditional SaaS applications are also becoming increasingly intelligent. Next, the dissertation recommends a portable ML microservice framework Minerva (also known as contAIn—second generation), a Micro-services-based container framework for Applied Machine learning as an efficient way to modularize and deploy intelligent microservices in both traditional “legacy” SaaS application suite and cloud, especially in the enterprise domain. The study also identified and discussed the needs, challenges, and architecture to incorporate ML microservices in such applications. Secondly, the study further identifies that there is an impetus to innovate quickly for machine learning features in enterprise SaaS applications. Minerva’s design for optimal integration with legacy and cloud applications using microservices architecture leveraging lightweight infrastructure accelerates deploying ML models in such applications. The study highlights the real-world implementation of Minerva, doubling innovation speed with the human resources. It evaluates ML model code reusability across applications, resulting in 1.15 to 2X faster adoption compared to previous methods in a marketing application suite. Minerva’s top-tier security encompasses several advanced features designed to protect sensitive data in SaaS marketing applications. It includes end-to-end data encryption, ensuring all data remains secure both in transit and at rest using robust cryptographic algorithms. While a layered design accelerated innovation through porting existing models to related business suites, generative AI methods, while promising, hadn't yielded significant gains with smaller models yet porting over already no code optimized model code.</p>

<p>Secure Access For Everyone (SAFE), is an integrated system for managing trust</p><p>using a logic-based declarative language. Logical trust systems authorize each</p><p>request by constructing a proof from a context---a set of authenticated logic</p><p>statements representing credentials and policies issued by various principals</p><p>in a networked system. A key barrier to practical use of logical trust systems</p><p>is the problem of managing proof contexts: identifying, validating, and</p><p>assembling the credentials and policies that are relevant to each trust</p><p>decision. </p><p>SAFE addresses this challenge by (i) proposing a distributed authenticated data</p><p>repository for storing the credentials and policies; (ii) introducing a</p><p>programmable credential discovery and assembly layer that generates the</p><p>appropriate tailored context for a given request. The authenticated data</p><p>repository is built upon a scalable key-value store with its contents named by</p><p>secure identifiers and certified by the issuing principal. The SAFE language</p><p>provides scripting primitives to generate and organize logic sets representing</p><p>credentials and policies, materialize the logic sets as certificates, and link</p><p>them to reflect delegation patterns in the application. The authorizer fetches</p><p>the logic sets on demand, then validates and caches them locally for further</p><p>use. Upon each request, the authorizer constructs the tailored proof context</p><p>and provides it to the SAFE inference for certified validation.</p><p>Delegation-driven credential linking with certified data distribution provides</p><p>flexible and dynamic policy control enabling security and trust infrastructure</p><p>to be agile, while addressing the perennial problems related to today's</p><p>certificate infrastructure: automated credential discovery, scalable</p><p>revocation, and issuing credentials without relying on centralized authority.</p><p>We envision SAFE as a new foundation for building secure network systems. We</p><p>used SAFE to build secure services based on case studies drawn from practice:</p><p>(i) a secure name service resolver similar to DNS that resolves a name across</p><p>multi-domain federated systems; (ii) a secure proxy shim to delegate access</p><p>control decisions in a key-value store; (iii) an authorization module for a</p><p>networked infrastructure-as-a-service system with a federated trust structure</p><p>(NSF GENI initiative); and (iv) a secure cooperative data analytics service</p><p>that adheres to individual secrecy constraints while disclosing the data. We</p><p>present empirical evaluation based on these case studies and demonstrate that</p><p>SAFE supports a wide range of applications with low overhead.</p> / Dissertation

Due to strong growth in the virtual business environment, online internationalization has become a topic of high interest. This makes it necessary for firms providing software online to carefully investigate and understand barriers and differences in countries before entering them. Further, companies expanding abroad face a variety of differences compared to their home market, which has to be carefully understood in order to succeed internationally and to avoid misinterpretations. This thesis took a qualitative approach and was based on six semi-structured interviews with open-ended questions, all performed with CEOs, founders or managers with explicit knowledge in the online internationalization phase of their firms. The insights from the interviews acknowledge which differences and barriers the firms faced and how they perceived them. The outline and result of the study were based on the four dimensions of cultural, administrative, geographic and economic challenges. The result showed that the cultural and geographic dimensions were barely perceived as barriers by the firms, the administrative dimensions moderately, whereas the companies clearly perceived the economic dimensions as barriers in their internationalization processes. Additional findings of the study were the importance of cultural leadership, hierarchies &amp; decision-making processes, high-density clusters and pricing strategies.

Consolidating patient and clinical data to support better-informed clinical decisions remains a primary function of electronic health records (EHRs). In the United States, nearly 6 million patients receive care from an accountable care organization (ACO). Knowledge of clinical decision support (CDS) tool design for use by physicians participating in ACOs remains limited. The purpose of this quantitative study was to examine whether a significant correlation exists between characteristics of alert content and alert timing (the independent variables) and physician perceptions of improved ACO quality measure adherence during electronic ordering (the dependent variable). Sociotechnical theory supported the theoretical framework for this research. Sixty-nine physician executives using either a Cerner Incorporated or Epic Systems EHR in a hospital or health system affiliated ACO participated in the online survey. The results of the regression analysis were statistically significant, R2 = .108, F(2,66) = 3.99, p = .023, indicating that characteristics of alert content and timing affect physician perceptions for improving their adherence to ACO quality measures. However, analysis of each independent variable showed alert content highly correlated with the dependent variable (p = .007) with no significant correlation found between workflow timing and the dependent variable (p = .724). Understanding the factors that support physician acceptance of alerts is essential to third-party software developers and health care organizations designing CDS tools. Providing physicians with improved EHR-integrated CDS tools supports the population health goal of ACOs in delivering better patient care.

Purpose: The aim of this thesis is to build a practical guide to get a clear understanding about the implementation process of Customer Relationship Management in the cloud within Small. It also describes the different concepts that are Customer Relationship Management, Cloud computing and CRM in the cloud, especially related to the SMEs, in order to have a great insight that gives the opportunity to implement successfully this paradigm.   Scientific method: The research lies in the interpretative field of inquiry. Abduction is used to combine empirical data with theoretical studies in orderto tryto investigate patterns that could give an understanding of the phenomena that is studied. Descriptive research approach using multiple-case study design is used.   Theoretical frame of references: The first part of the theoretical frame of references explores existing theories. This leads to CRM and Cloud Computing. The second part explores different means of analysing our problematic.   Empirical method: The chosen approach is qualitative. Interviews have been conducted for data collection. Documentsarehave beengathered and analysed to support the interviewguides. We also gathered a previous practical guide from Salesforce in order to compare our results.   Analysis: Analysing hosted CRM implementation of three SMEs using Salesforce, it describes the key facts that have to be taken into account to implement the Salesforce CRM solution.   Conclusion: The findings show how three companies can be analysed to draw conclusions about the implementation process. According to interviews, theories, documents from hosted CRM provider, some suggestions have been advised to avoid problems concerning the implementation in SMEs.

In general, a common reference architecture can be derived for Software as a Service (SaaS) architecture. However, while designing particular applications one may derive various different application design alternatives from the same reference SaaS architecture specification. To meet the required functional and nonfunctional requirements of different enterprise applications it is important to model the possible design so that a feasible alternative can be defined. In this thesis, we propose a systematic approach and the corresponding tool support for guiding the design of the SaaS application architecture. The approach defines a SaaS reference architecture, a family feature model and a set of reference design rules. Based on the business requirements an application feature model is defined using the family feature model. Selected features are related to design decisions and a SaaS application architecture design is derived. By defining multiple application architectures based on different application feature models we can even compare multiple alternatives and based on this select the most feasible alternative.