Software Business

Organizations must gain insights into often fragmented and isolated data assets and overcome data silos to profitably leverage data as a strategic resource. Data catalogs are an increasingly popular approach to achieving these objectives. Despite the perceived importance of data catalogs in practice, relatively little research exists on how to design corporate data catalogs. It is also obvious that the existing market solutions have to be customized to the specific organizational needs. This paper presents a list of functional requirements for enterprise data catalogs extracted from a systematic literature review. The requirements can be used to frame and guide more specific research on data catalogs as well as for system selection and customization in practice.

In the current scenario of digital transformation, understanding the interaction between the areas of business and software architecture is essential for delivering successful projects. This research aims to elucidate perceptions related to both domains, thus seeking a more efficient collaboration in the context of agile software development projects. Based on a qualitative research method, we conducted semi-structured interviews with product owners and software architects. The collected data were analyzed using Thematic Analysis to discover patterns and themes regarding the perceptions of the interviewed professionals. We found out that business areas often have a limited understanding of the technical complexities involved in software architecture, while software architects sometimes have no knowledge about business development plans. However, a continuous iteration process, supported by proper communication channels, could drive better project results. The study also revealed the potential for a proactive, integrated approach to architecture, focusing on continuous education and team alignment. Finally, bridging the knowledge gap and fostering collaboration between the two areas may lead to more efficient and effective software development processes. Future research perspectives could reveal strategies that would improve this collaboration or explore similar dynamics in different organizational contexts.

Software ecosystems (SECO) affect requirements management when considering multiple actors (i.e., keystone, third-party developer, users) from different organizations using several communication channels such as issue trackers and forums. To deal with this scenario, professionals involved in requirements management in SECO have resorted to several open innovation (OI) practices. Our study aims to investigate OI practices applied to support requirements management in SECO. We conducted a field study based on interviews with 21 professionals involved in requirements management activities in SECO. We identified 10 OI practices to support requirements management in SECO and 14 communication channels to receive/provide requirements from/to external actors. OI practices identified in this study can help practitioners manage requirements in the SECO context in which they are engaged, making this process more informal, open, and collaborative.

CONTEXT: Successful agile teams advance their work practices continuously. The continuous improvement of effective tool-based requirements practices is an important foundation of business agility. However, requirements tool practices are still widely rooted in plan-based approaches. They are not yet suited well for agile teams or agile businesses. OBJECTIVE: Report and make available an approach for continuous improvement of requirements practices so that tool-based requirements management can drive business agility. METHOD: Industry experience report based on a series of cases from different sources, including ones with involvement of the author. RESULTS: Processes and work practices for evolutionarily introducing and adapting requirements tools and tool-based requirements practices, in a way that supports business agility. CONCLUSION: The presented practices can guide organizations towards establishing effective, tool-based requirements practices that support business agility. A foundation is laid for further systematic investigation and development of the approach.

The public sector is a significant consumer of ICT systems. In countries like Finland, where openness, objectivity, and fairness in public acquisitions are deemed essential, public ICT procurement is based on tenders initiated by public sector organizations. The tendering process is regulated by laws that aim to eliminate unfair advantages and provide all potential stakeholders with similar opportunities to participate. However, depending on the stakeholders’ perspectives, they may interpret the tendering process differently, leading to tensions among them. In this paper, we examine Finland’s public procurement of ICT systems using semi-structured interviews as our data collection method and analyze the results thematically. The interviewees include individuals familiar with tendering and acquisition processes in public organizations and those involved in delivering systems as vendors, representing two different perspectives on the tendering process. The results indicate that although there are significant differences in maturity among public sector organizations participating in procurement, several common themes emerged from nearly all the interviews. Furthermore, in light of contrasting views between public organizations and vendors, recurring tensions arise due to different interpretations of acquisition laws.

Enterprise architecture (EA) is infamous for implementation problems and unredeemed promises. Imprecise and unstandardized EA work practices and various definitions make it difficult to comprehend what should be done and how, and to advance digital transformation. Earlier studies have identified communication and collaboration challenges as one of the most common and fatal sources of problems. In this paper, we study how different actions help avoiding and addressing communication and collaboration problems in EA projects. We conduct a qualitative and comparative case study of three public sector EA projects in Finland. Our data is based on ethnographic observations, which were later inductively analyzed. As an outcome, we present a theoretical explanation of the phenomenon and make three propositions to manage and possibly overcome the problem.

In-house procurement is a controversial issue in the field of public procurement. Simply put, such procurement allows overlooking certain aspects of fair and equal treatment of vendors. This paper presents qualitative research on in-house ICT procurement within Finnish municipalities. Semi-structured interviews were conducted to gather insights from municipal stakeholders. Using grounded theory approach, data analysis shows intricate dynamics between Finnish municipalities and in-house entities associated with them. Still, it is clear that the legal framework governing in-house procurement remains intricate and debated .

In modern business, maintaining competitiveness and efficiency necessitates the integration of state-of-the-art technology. This paper introduces the Artificial Intelligence Procurement Assistant (AIPA), an advanced system co-developed with Solita, a Finnish software company. AIPA leverages Large Language Models (LLMs) and sophisticated data analytics to enhance the assessment of procurement call bids and funding opportunities. The system incorporates LLM agents to enhance user interactions, from intelligent search execution to results evaluation. Rigorous usability testing and real-world evaluation, conducted in collaboration with our industry partner, validated AIPA’s intuitive interface, personalized search functionalities, and effective results filtering. The platform significantly streamlines the identification of optimal calls by synergizing LLMs with resources from the European Commission TED and other portals. Feedback from the company guided essential refinements, particularly in the performance of ChatGPT agents for tasks like translation and keyword extraction. Further contributing to its scalability and adaptability, AIPA has been made open-source, inviting community contributions for its ongoing refinement and enhancement. Future developments will focus on extensive case studies, iterative improvements through user feedback, and expanding data sources to further elevate its utility in streamlining and optimizing procurement processes.

To remain vital, a digital platform ecosystem requires governance. In the extant literature a platform ecosystem typically has a single focal actor who is responsible for the governance. We conducted a case study in heavy industry to understand how the responsibilities of a focal actor in governing a business-to-business platform ecosystem are shared and how they change. We observe the division of responsibilities and their changes as configurations. We conclude that the focal actor’s responsibilities in a platform ecosystem are more multifaceted than the established view where a single actor has a stable set of responsibilities. The division of responsibilities in an ecosystem is subject to actor strategies and their positions in the supply chain. Thus, the strategic moves in an ecosystem are not made by a single actor but by multiple focal actors with multiple strategies.

Online user feedback has become an essential mechanism for software organizations to gain insight into user concerns and to recognize areas for improvement. In software platform ecosystems, staying abreast of user feedback is particularly challenging due to the multitude of feedback channels and the complex interplay with third party applications. In this paper we report from a mixed-method study of user feedback from over 40,000 relevant reviews from 139 SECO platforms out of 2.4 million online user reviews scraped from 283 retrieved SECO platforms. Through thematic analysis and machine learning classifiers with high accuracy, we identified and analyzed six categories of user challenges in the areas of Integration, Customer Support, Design & Complexity, Privacy & Security, Cost & Pricing, and Performance & Compatibility. Our analysis also shows a significant growth of SECO user feedback in the past five years, highlighting the importance of understanding such user feedback as well as research methodologies to automatically study online user concerns in software ecosystems. To further understand mitigation strategies for challenges reported by end users, we interviewed four executives from large ecosystems and describe strategies in addressing those identified challenges. This research is a first large scale study of user feedback in software ecosystems; the categories of user concerns are hopefully useful in guiding platforms in designing and fostering better software ecosystems. Our methodology for automatically classifying the user feedback that is SECO-related can also serve as guidance for future studies that can further advance our understanding of user feedback and how to integrate it into improved software ecosystems.

Sharing data among public institutions is essential for reaping the benefits of data-driven capabilities. Literature to date has identified several types of benefits that are likely to accrue to a wide range of sectors, as well as challenges and obstacles to implementing data-sharing solutions. We sought to identify perceptions of possible benefits, likely challenges, and the likelihood of overcoming them in the Norwegian public sector. Our survey of IT practitioners interested in the subject suggests that optimism about data sharing is high, concerns about a wide range of challenges are also high, and confidence in public institutions is tenuous. Responses also suggest that divisional management may be critical in implementing data sharing solutions. The pattern of responses suggests uncertainty consistent with low maturity in the field. We posit that data sharing among public institutions is part of a broader set of capabilities needed for public service innovation across institutions.

Despite the growing discussion and concern about the topic, gender diversity in the Exact Sciences and Technology still requires attention. It has been observed by several authors that gender diversity is not present in a significant way in development teams, despite the potential positive effects. Moreover, with the growing demand for software that meet complex business needs, the concept of Software Ecosystems (SECO) has emerged and opens opportunities for external developers and strategies for fostering gender diversity. A Proprietary Software Ecosystem (PSECO) is a type of SECO that comprises a common technological platform with contributions protected by intellectual property. This work aims to investigate which barriers women face in software development teams focusing on the context of PSECO and what strategies can be used to increase inclusion based on a multivocal literature review. To do so, 29 studies were selected and 13 gender barriers were identified, with the 3 most cited barriers being: sexism, lack of peer parity, and imposter syndrome. Furthermore, it was observed that external PSECO actors can significantly interfere in the occurrences of gender barriers, in addition to the internal actors of the central organization (keystone).

Business and technology are intricately connected through logic and design. They are equally sensitive to societal changes and may be devastated by scandal. Cooperative multi-robot systems (MRSs) are on the rise, allowing robots of different types and brands to work together in diverse contexts. Generative artificial intelligence has been a dominant topic in recent artificial intelligence (AI) discussions due to its capacity to mimic humans through the use of natural language and the production of media, including deep fakes. In this article, we focus specifically on the conversational aspects of generative AI, and hence use the term Conversational Generative artificial intelligence (CGI). Like MRSs, CGIs have enormous potential for revolutionizing processes across sectors and transforming the way humans conduct business. From a business perspective, cooperative MRSs alone, with potential conflicts of interest, privacy practices, and safety concerns, require ethical examination. MRSs empowered by CGIs demand multi-dimensional and sophisticated methods to uncover imminent ethical pitfalls. This study focuses on ethics in CGI-empowered MRSs while reporting the stages of developing the MORUL model.

In the evolving field of Agile Project Management (APM), the role of the project manager is in transition. This paper identifies common ‘pain points’ in APM through a literature review and constructs a theoretical model to address them. The study introduces ‘Prompt Engineering’ as a novel approach to leverage artificial intelligence (AI), specifically ChatGPT, for mitigating these challenges. Empirical research evaluates ChatGPT's capabilities and reliability in managing various project tasks using engineered prompts. The findings suggest that while ChatGPT cannot fully replace human project managers, it excels in assisting, guiding, and automating specific tasks when guided by well-crafted prompts. As an outcome, prompt engineering patterns for project managers is proposed to facilitate the application of AI in agile settings. In this paper, we introduce patterns for requirements management, stakeholder and management teams and role clarification. The paper concludes that ChatGPT's knowledge is generally reliable but emphasizes the need for expert evaluation in critical areas.

Hackathons are themed, fast-paced events where participants gather in teams to work on a project of their interest. Hackathons are often organized to drive entrepreneurial behavior, however, little is known about how they have supported startup creation. To address this issue, we conducted a cross-sectional survey among hackathon participants about their motivations for participating in a hackathon including creating a new startup product and advancing their careers. The survey also addressed their perceived hackathon benefits related to entrepreneurship, such as learning and networking, and how useful they were to their startups. Moreover, the survey included aspects of the hackathon setting that may have influenced startup creation, including winning awards. We obtained answers from participants who have attended 48-h, in-person hackathons. We found motivations related to entrepreneurship that were related to startup creation, such as learning about the startup domain. Our findings show that participants with entrepreneurial motivations are more likely to create a startup after the hackathon. We also found that participants with startups in an early stage have attended hackathons motivated to build the initial version of their startup product, however, they have also worked on other projects unrelated to their startup. To support startup creation beyond hackathons, organizers should gain awareness of such hackathon participants who are motivated by entrepreneurship.

In software engineering research, academia-industry collaboration is predominantly understood as partnerships between academic institutions and large companies. Small and Medium-sized Enterprises (SMEs) are vital contributors to the industry, and they are numerous. Their unique preconditions and challenges differentiate their collaboration dynamics from larger corporations. We seek to identify guiding principles and practices for initiating collaborations between researchers and SMEs. Through a meta-synthesis approach drawn from two systematic literature reviews, we introduce a collaborative model canvas. This emphasizes the importance of SMEs’ business contexts and the relationships between researchers and SMEs. Our research offers insights for those looking to collaborate with SMEs, considering potential challenges and limitations.

The increasing integration of artificial intelligence (AI) into software engineering (SE) highlights the need to prioritize ethical considerations within management practices. This study explores the effective identification, representation, and integration of ethical requirements guided by the principles of IEEE Std 7000–2021. Collaborating with 12 Finnish SE executives on an AI project in autonomous marine transport, we employed an ethical framework to generate 253 ethical user stories (EUS), prioritizing 177 across seven key requirements: traceability, communication, data quality, access to data, privacy and data, system security, and accessibility. We incorporate these requirements into a canvas model, the ethical requirements canvas. The canvas model serves as a practical business case tool in management practices. It not only facilitates the inclusion of ethical considerations but also highlights their business value, aiding management in understanding and discussing their significance in AI-enhanced environments.

AI ethics has become a common topic of discussion in both media and academic research. Companies are also increasingly interested in AI ethics, although there are still various challenges associated with bringing AI ethics into practice. Especially from a business point of view, AI ethics remains largely unexplored. The lack of established processes and practices for implementing AI ethics is an issue in this regard as well, as resource estimation is challenging if the process is fuzzy. In this paper, we begin tackling this issue by providing initial insights into the cost of AI ethics. Building on existing literature on software quality cost estimation, we draw parallels between the past state of quality in Software Engineering (SE) and the current state of AI ethics. Empirical examples are then utilized to showcase some elements of the cost of implementing AI ethics. While this paper provides an initial look into the cost of AI ethics and useful insights from comparisons to software quality, the practice of implementing AI ethics remains nascent, and, thus, a better empirical understanding of AI ethics is required going forward.

Health-tech startups are essential, as they provide cutting-edge solutions to numerous healthcare concerns in the rapidly evolving healthcare industry. They use various technologies to create solutions that boost and advance healthcare systems and healthcare delivery. Open-source software (OSS) technology has become an essential component of startups’ toolkits, providing various advantages, such as free access to source codes and opportunities for innovation. Research on OSS in healthcare startups is limited, so our study aims to investigate how health-tech startups perceive the influence of OSS on product development and to identify the challenges they face. To meet this objective, we conducted an empirical study with six health-tech startups, using semi-structured interviews. Thematic analysis was performed on the collected data to identify common themes and subthemes related to the research objective. The findings showed that health-tech startups benefit from the cost efficiency, scalability, and customization of OSS. Open-source software tools, reshape development and promote efficient code management, provide community support, and reduce costs. However, they demand OSS knowledge, management of updates, regulatory compliance, and heightened cybersecurity. Our study adds to the body of knowledge on OSS and healthcare startups and the connection between them. We provide recommendations for health-tech startups, such as embracing OSS tools for their benefits, investing in education and training, and engaging with the OSS community for comprehensive support in their product development processes.

Many incumbents observe the startup world in jealousy of their agility and innovational performance. An increasing number of initiatives aim to mimic startup-like procedures in order to increase the incumbents’ innovational output. Structural models like accelerators, spinoffs, incubators, or corporate venture capitals aim to achieve that goal by implementing different governance setups. However, the success of such initiatives often remains unclear. While there is broad research on such topics, a clear empirical view on governance mechanisms for entrepreneurial structures in incumbents is missing. This paper outlines how to build a governance model based on empirically validated mechanisms and their relationship to corporate startup autonomy. This is achieved by following the systematic literature review approach by Webster and Watson combined with qualitative data analysis techniques. The results describe relevant gaps in current research and identify promising pathways for future research.

The increasing significance of social and environmental impact within the technology startup business sector has garnered attention. Previous research has explored impact investing and related themes in the startup context. However, despite the growing interest in this area, a noticeable gap exists in research addressing impact investing ecosystems (IIE) and ecosystem-related challenges and advantages specifically within the technology field. This study endeavors to fill this gap by examining organizations within the Finnish IIE, bridging the divide between current industry practices and academic research. This study employed an interview-based approach, featuring thirteen interviewees representing eleven participating organizations. These interviews followed a semi-structured format, with all interviewees holding roles closely linked to the technology startup context within the Finnish IIE. Utilizing the thematic synthesis approach, this research aims to elucidate the perceived challenges faced by technology startups operating within the IIE. The findings of this study underscore the diversity and multiplicity of challenges confronting startups within the IIE, spanning various functions and operations, as well as the existing financial structures. Furthermore, this study puts forth recommendations for mitigating these perceived challenges and suggests potential avenues for future research within this domain.

Software startup companies operate under extreme conditions of uncertainty and with limited resources. These innovative companies face constant pressure to find a product-market fit, drive growth, and maintain competitive advantage. The nature of these companies makes them suitable candidates to practice analytics. Analytics can help software startups to use data in several ways e.g. make data-informed decisions, grow business, and provide value to users. However, startup founders tend to put off practicing analytics for a later time. In addition, the existing literature on startups does not provide paved paths to establish analytics in the context of startups. Therefore, to this end, we perform a gray literature review, to understand what startup practitioners say about analytics benefits and how can startups define analytics within their particular context. We utilized YouTube as a source of our data. After applying inclusion and exclusion criteria to 400 videos, we ended up analyzing 16 potentially relevant videos. We used thematic synthesis as well as quasi-statistics to analyze the data. Our results identify and report ten analytics benefits, and two key analytics practices to set up analytics in these competitive environments.

Cybersecurity is becoming increasingly important from a software business perspective. The software that is produced and sold generally becomes part of a complex landscape of customer applications and enlarges the risk that customer organizations take. Increasingly, software producing organizations are realizing that they are on the front lines of the cybersecurity battles. Maintaining security in a software product and software production process directly influences the livelihood of a software business. There are many models for evaluating security of software products. The product security maturity model is commonly used in the industry but has not received academic recognition. In this paper we report on the evaluation of the product security maturity model on usefulness, applicability, and effectiveness. The evaluation has been performed through 15 case studies. We find that the model, though rudimentary, serves medium to large organizations well and that the model is not so applicable within smaller organizations.

The role of software product management is key for building, implementing and managing software products. However, although there is prominent research on software product management (SPM) there are few studies that explore how this role is rapidly changing due to digitalization and digital transformation of the software-intensive industry. In this paper, we study how key trends such as DevOps, data and artificial intelligence (AI), and the emergence of digital ecosystems are rapidly changing current SPM practices. Whereas earlier, product management was concerned with predicting the outcome of development efforts and prioritizing requirements based on these predictions, digital technologies require a shift towards experimental ways-of-working and hypotheses to be tested. To support this change, and to provide guidelines for future SPM practices, we first identify the key challenges that software-intensive embedded systems companies experience with regards to current SPM practices. Second, we present an empirically derived framework for strategic digital product management (SPM4AI) in which we outline what we believe are key practices for SPM in the age of AI.

Experimentation has been considered critical for successful software product and business development, including in video game startups. Video game startups need “wow” qualities that distinguish them from the competition. Thus, they need to continuously experiment to find these qualities before running out of time and resources. In this study, we aimed to explore how these companies perform experimentation. We interviewed four co-founders of video game startups. Our findings identify six practices, or scenarios, through which video game startups conduct experiments and challenges associated with these. The initial results could inform these startups about the possibilities and challenges and guide future research.

DevOps is a team culture and organizational practice that eliminates inefficiencies and bottlenecks in the DevOps infrastructure. While many companies are adopting DevOps practices, it can still be risky. We conducted 26 interviews with DevOps professionals around the globe and found four major risks associated with DevOps practices: Organizational risks (Intra-organizational collaboration and communication, strategic planning), Social and cultural risks (Team Dynamics, Cultural shift), Technical risks (Integration, Build and test automation), Ethics and security breaches in DevOps environment (Ethical risks, Data collection ethics, Ethical decision making). Our research also identified several risk mitigation strategies namely continuous testing, using infrastructure as code, security audit and monitoring, disaster recovery planning, cross-functional training, proper documentation, continuous learning, continuous improvement etc. that companies can adopt for better performance and efficiency.

This paper explores the connection between agile methods and digital customer experience, aiming to identify what are the hallmarks of a good agile way of working. The research is an exploratory case study consisting of interviews and analysis. In summary, the research suggests that the hallmarks of a good agile way of working are 1) breaking down tasks into sufficiently small pieces, 2) defining tasks precisely and releasing them to production evenly, 3) continuous improvement, and 4) good planning of sprints. These good agile operating methods can be seen in the development measures as a short lead time, a short time to export to production, low errors, and a high deployment frequency. According to the findings, these metrics are linked to the Net Promoter Score (NPS), a measure of customer experience. A team with sufficient technical capabilities team that utilizes agile operating methods is able to produce the desired things for customers at exactly the right time while constantly improving, so that the NPS is positive, and its direction is improving. On the other hand, the team’s bad operating methods are also visible in the NPS meter – in this case, the NPS fluctuates strongly. Teams can obtain insightful supplementary data about their own practices by keeping track of development measures.

Secure and agile development of operational technology (OT) and related software in industry is a crucial but challenging issue. Generally recognized standards such as IEC 62443–4-1 set up the requirements for cybersecurity processes for OT and software development. The main challenge of IEC 62443–4-1 resides in its adoption and implementation in practice, which originates from the standard’s complexity. We propose three novel design principles and two subsequent design objectives to be prioritized for future design-research oriented work on standard-compliant DevSecOps. The design principles have been formed after six years of experience and observations in cybersecurity consulting in industry, documented here as a piece of action design research (ADR). As a case study, we describe instantiation of the design principles at Valmet Automation Systems, one of the earliest IEC 62443–4-1 -certified companies. The proposed design principles altogether suggest for the information-centric view on the contextual adoption and use of the IEC 62443–4-1 standard in DevSecOps practices for OT.

Establishing a psychologically safe work environment is crucial for leading a positive and practical agile retrospective. Emotions are closely intertwined concepts that come under the roof of psychology. Capturing them at the right time helps to detect harmful or favourable online behaviours, hinder or facilitate the software development cycle, and moralize or demoralize the team in a software company. This study aims to identify emotions that appear during the online agile retrospective. Our study asks the research question: How often are different emotions repeated during the online agile retrospective? We conducted a multiple case study with two software companies. We analyzed three recorded online retrospective sessions to seize various emotions. Our findings show that eighteen emotions appear on the agile retrospective. Some of the highest repeated emotions are approval, realization, excitement, relief, disappointment, confusion, optimism, and disapproval.

The metaverse has been considered in various literature reviews as a multifaceted and complex concept that can not be defined from a single set of terms. These literature reviews have attempted the Metaverse definition based on the research most published before the heated attention on the Metaverse in 2021; therefore, they may not provide an up-to-date understanding of the phenomenon that incorporates the perspectives from the industry. This paper aims to disentangle the complexity of the Metaverse concept considering the perspectives of insiders - practitioners who play essential roles in the recent Metaverse wave. To achieve our goal, we analyzed one specific type of gray literature - a podcast series from Bloomberg entitled “Into the Metaverse” which featured different professionals active in the Metaverse landscape. Three themes were identified that represent the essential characteristics of the Metaverse which include technology capabilities, infrastructure characteristics, and social and economic aspects. Our study contributes to a more contemporary industrial understanding of the Metaverse concept. The understanding can assist researchers in future investigations into the evolving Metaverse paradigm.

Through non-financial reporting, such as CSRD, carbon footprint calculations are becoming mandatory in the software industry. The golden standard for reporting CO2 emissions is based on the Greenhouse Gas (GHG) Protocol and its scopes 1, 2, and 3. However, as a producer of purely digital products, the software industry differs from traditional industries in its carbon footprint. The software industry value chain relies heavily on an infrastructure that can contribute most of its emissions. It has been recognized that there is a need for an industry-customized carbon emissions model that considers the software industry's peculiarities. The primary goal of this study is to define the main sources of climate impacts in the software industry and propose a model of the GHG Protocol adaptation to software companies. This research has been done in our Green ICT project and is based on interviews done in that project. The data for this research was collected from five software companies with different demographics and business models. The interviews, with a total amount of 14, were conducted between November 2022 and March 2023 during a service design process of an automated tool that facilitates green transition in software companies. The analysis of the interviews was supplemented with the results from four multi-stakeholder workshops conducted during the service design process, as well as with the analysis of a series of webinars around the topic. As a result of the study, the Software Company Scopes model for the primary sources of greenhouse gas emissions in the software company and its value chain was created, and the GHG Protocol was tailored to the needs of the software industry. Thus, considering its industry-specific peculiarities, we may conclude that the GHG Protocol can be applied to the software industry.

The advent of serverless computing has revolutionized the landscape of cloud computing, offering a new paradigm that enables developers to focus solely on their applications rather than managing and provisioning the underlying infrastructure. These applications involve integrating individual functions into a cohesive workflow for complex tasks. The pay-per-use model and nontransparent reporting by cloud providers make it difficult to estimate serverless costs, impeding informed business decisions. Existing research studies on serverless computing focus on performance optimization and state management, both from empirical and technical perspectives. However, the state-of-the-art shows a lack of empirical investigations on the understanding of the cost dynamics of serverless computing over traditional cloud computing. Therefore, this study delves into how organizations anticipate the costs of adopting serverless. It also aims to comprehend workload suitability and identify best practices for cost optimization of serverless applications. To this end, we conducted a qualitative (interviews) study with 15 experts from 8 companies involved in the migration and development of serverless systems. The findings revealed that, while serverless computing is highly suitable for unpredictable workloads, it may not be cost-effective for certain high-scale applications. The study also introduces a taxonomy for comparing the cost of adopting serverless versus traditional cloud.

The emergence of quantum computing proposes a revolutionary paradigm that can radically transform numerous scientific and industrial application domains. The ability of quantum computers to scale computations imply better performance and efficiency for certain algorithmic tasks than current computers provide. However, to gain benefit from such improvement, quantum computers must be integrated with existing software systems, a process that is not straightforward. In this paper, we investigate the quantum computing ecosystem and the stakeholders involved in building larger hybrid classical-quantum systems. In addition, we discuss the challenges that are emerging at the horizon as the field of quantum computing becomes more mature.

Amidst the evolving crises and disruptions threatening firms’ competitiveness, businesses are faced with increased dynamism necessitated by technological development, digitalization, and sustainability requirements for survival and growth. This study delves into the intersection of dynamic capabilities (DC), digital transformation (DT), and sustainable resilience among law firms in developing countries. With Nigerian law firms as our case study, this research investigates the strategic integration of dynamic capabilities and digital transformation to foster long-term sustainability of law firms’ resilience during a crisis. Through empirical analysis and qualitative exploration, the study unveils obstacles ranging from digital resistance to technical constraints yet uncovers valuable insights from adopting innovative digital strategies that enhance operational resilience and contribute to driving positive economic, environmental, and social impact while ensuring long-term sustainability objectives. The study reaffirms the significance of dynamic capabilities for digital transformation and contributes to the broader discourse on how digital technology enables firms in emerging economies to maneuver disruptions during crises.

Digital Transformation (DT) strives to alter an entity by substantially changing its characteristics facilitated by integrating digital technologies. Albeit numerous barriers hinder the realization of its potential. Barriers are subject to scientific research. Generally, scientific works result in research streams. The existing literature already examines the DT streams. Although these works make an essential contribution, they cannot sufficiently explore the field of barriers. Keeping track of the concepts and themes in a growing research field is challenging. Therefore, the aims of this mapping study are (1) to show which domain-specific research streams are explicitly dealing with the DT barriers, (2) to highlight which topics research currently addresses, and (3) which topics should be investigated in the future. Combining elements of a bibliometric analysis with a systematic literature review, we mapped nine different streams based on 203 publications. The results indicate that much research focuses on industrial companies or sectors but needs an overarching perspective. Also, many studies are only concerned with identifying the barriers, while systematic approaches to overcoming them still need to be developed.