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The purpose of this paper is to describe how the logic model can provide infrastructure for library programming from planning, tracking accomplishments, identifying where adjustments are required, to reporting outcomes.

The National Network of Libraries of Medicine, MidContinental Region has used the logic model since 2003 for planning and organizing its work. Its geographically dispersed librarians carry out six project initiatives. The logic model is used during planning to establish consensus on expectations and responsibilities. An online reporting tool, developed in 2004, tracks staff activities to the logic model. Quarterly reports for each project uses reporting tool data to determine whether the project is going along as planned or whether an intervention is required. At the end of the year, a final report assesses the achievement outcomes and indicators.

Writing a logic model is a study in semantics. It is important to be as specific as possible. Accurately defining terms saves puzzlement down the line on whether an activity was carried out as planned or an indicator was met. Measurable targets for each indicator encourage staff to continuously evaluate their activities and adjust their work to achieve the desired results. Writing realistic indicators is a process that improves with practice. Early in the program enthusiasm and the optimism of the librarian staff led to the indicators that were unrealistic within a one year timeframe.

The logic model accommodates the unforeseeable and helps evaluate whether an activity is worth doing. It is impossible to identify all future opportunities. The logic model runs from the visionary (goals) to the ordinary (activities). When the unexpected arises it can be evaluated on how closely it addresses goals and outcomes and can be tied to that goal or outcome when reporting. The integration of the logic model into the program is made more efficient with an online report system. Having a system that links staff work to the logic model facilitates analysis, decision making, and reporting.

The logic model is generally touted as a planning tool. This paper expands the use of the logic model as a tool for planning, tracking, and reporting.

The purpose of this paper is to introduce a new business model logic, highlighting value processes in and properties of platform business models to inform business model thinking from a systemic and dynamic perspective. It challenges the idea of firms managing, influencing and controlling entire activity systems.

The study traces the evolution of different approaches to business models and assesses theories that explain value cocreation and systemic value capture to develop a new business model logic.

Business model thinking has evolved away from Porter’s value chain to a new logic based on open networks and platforms. This study develops a framework for understanding platform business models from a systemic perspective. Derived from service-dominant logic, this new business model logic responds to phenomena in contemporary business environments characterized by increasing connectivity and sociality among actors.

The framework, developed from an extensive body of business model literature, has yet to be subjected to empirical investigation. Future research may involve the exploration of business model design processes and business model innovation from a systemic perspective.

Managers who aim to design their business models based on the logic of platform businesses require an understanding of their organization’s collaboration potential, technological interfaces and potential to leverage network relationships. This research guides start-ups and incumbents to evaluate their platform potential.

This study systematically emancipates the business model logic from a firm-centered, inside-out perspective, focuses on network relationships beyond the customer–firm dyad, explains value processes beyond organizational borders and rethinks value capture from a systemic perspective.

The purpose of this study is to develop a service logic oriented framework for business model development. “Service logic” covers the basic principles of the three contemporary customer value focused business logics: service-dominant logic, service logic and customer-dominant logic.

This study is based on an empirical qualitative research and deployed the focus group method. The data are generated in a series of interactive co-creative focus group workshops involving both practitioners and academics.

As the outcome, a new tool was developed, called Service Logic Business Model Canvas. The new canvas is a modified version of the original Business Model Canvas (Osterwalder and Pigneur, 2010).

This study adopts service logic in business model thinking and increases knowledge on how to keep the customer needs in the centre of business model development.

The developed canvas makes the theory of service-dominant logic tangible and easily applicable in practice. It enables service innovation truly based on customer value by ensuring that the customer is in the centre of all the elements of a business model. It can function both as a rapid prototype of a new business model and as a communication tool that quickly illustrates the company’s current business model. It can also help in creating a customer-centred business culture. It is designed to be applied to each customer profile separately, thus enabling a deeper understanding of the customer logic of each relevant profile.

Earlier business model frameworks tend to be provider-centric and goods-dominant, and require further development and adaptation to service logic. This study adopts service logic in business model thinking. It embeds the true and deep customer understanding and customer value in each element of the business model, and contributes to both business model and service-dominant logic literature.

While balanced scorecards, strategy maps, and causal linkage models have been applied extensively by profit organizations over the last two decades, a similar approach to analysis, called logic models, has been increasingly applied by non-profit and other social-purpose organizations. This chapter provides a discussion of the basics of logic models and shows their application in three different settings, which include personal improvement, the social impact of business schools, and corporate governance. The chapter also provides an extensive discussion on field research and a case study of a leading international business school, wherein logic models were applied followed by social impact measurement. Finally, the chapter includes suggestions for future research that is needed to improve the applications of logic models and social impact measurement and the success of social-purpose organizations including business schools.

The main objective of this paper is to show how fuzzy logic and multiple regression analysis (MRA) techniques can be used by construction companies for determining the size of contingency that will be included in bid prices for international construction projects in a more systematic way and to compare their modelling performances.

The steps followed in the execution of this study mainly consists of: conducting a literature review on international construction in order to identify the factors that may affect contingency amounts that will be included in bid prices for international construction projects; developing the general framework of the proposed contingency estimation model; designing a questionnaire based on the information gathered from the literature review, delivering these questionnaires to construction experts, and obtaining the actual data of 36 international construction projects; developing a fuzzy logic model based on expert judgments and three multiple regression analysis models (MRAM) using the collected data; and comparing the performances of these approaches.

In this study, a fuzzy logic model and three MRAM were developed. Their modelling performances were compared using actual data obtained from 36 international construction projects that had been completed by 20 large-scale Turkish construction companies in 14 different countries. It is found that the developed fuzzy logic model outperforms the MRAM built for the studied projects.

This study shows that fuzzy logic and MRA techniques can be successfully used by construction companies, which predominantly do business in foreign countries, for estimating the size of cost contingency that will be included in bid prices for international construction projects. The modelling performances of fuzzy logic and MRAM are also compared.

The purpose of this paper is to study how digital business models evolve when entrepreneurs move to new digital platforms and how this evolution is related to effectuation and causation logics.

This study applies a multiple case study approach to investigate how digital business models change in small, Japanese high-tech firms providing their innovations through different digital platforms. To investigate digital business models, this study considers the elements that comprise general business models. The case firms were selected based on size, products and transitions from physical to various digital platforms. Semi-structured interviews were conducted with the key decision-makers from the case firms.

The findings show that through digital transformation, the case firms’ digital business models evolved by following effectuation logic as well as causal logic. All the firms employed causal logic when moving to new platforms, among other actions. The case firms used effectual logic with success for product development and adjustments to their network. Especially firms providing video games relied on effectuation for high impact products. Effectual logic did not play a role at all in changes to value delivery and had only little impact on revenue structures.

This research helps understand how digitalization of platforms and subsequent moves to newer digital platforms improve a firm by changing the business model elements through effectuation and causation logics. This research extends the understanding of digital business model transformation to a more granular level, business model elements.

Repetitive projects play an important role in the construction industry. A crucial point in scheduling this type of project lies in enabling timely movement of crews from unit to unit so as to minimize the adverse effect of work interruptions on both time and cost. This paper aims to examine a repetitive scheduling problem with work continuity constraints, involving a tradeoff among project duration, work interruptions and total project cost (TPC). To enhance flexibility and practicability, multi-crew execution is considered and the logic relation between units is allowed to be changed arbitrarily. That is, soft logic is considered.

This paper proposes a multi-objective mixed-integer linear programming model with the capability of yielding the optimal tradeoff among three conflicting objectives. An efficient version of the e-constraint algorithm is customized to solve the model. This model is validated based on two case studies involving a small-scale and a practical-scale project, and the influence of using soft logic on project duration and total cost is analyzed via computational experiments.

Using soft logic provides more flexibility in minimizing project duration, work interruptions and TPC, especial for non-typical projects with a high percentage of non-typical activities.

The main limitation of the proposed model fails to consider the learning-forgetting phenomenon, which provides space for future research.

This study assists practitioners in determining the “most preferred” schedule once additional information is provided.

This paper presents a new soft logic-based mathematical programming model to schedule repetitive projects with the goal of optimizing three conflicting objectives simultaneously.

Although business incubators are widely used support mechanisms for innovative entrepreneurship, the literature still lacks theoretically based explanations of how the incubation process creates value for stakeholders. This study aims to address this gap by developing a conceptual model, and related research propositions, that explains how the entrepreneurial logic in use by an incubator influences the incubation process (selection criteria and service offering) and performance.

Integrating the effectuation and entrepreneurial opportunities literature, which shares common conceptualizations about how the predictability of the future affects entrepreneurial action, the authors posit two archetypes of entrepreneurial logic that are associated with different incubation processes (causal or effectual) and two archetypes of opportunity attributes (discovery- or creation-based) that affect the incubation process needed to support their development.

Juxtaposing these archetypes, the proposed cross-level conceptual model specifies four levels of fit (ideal, surplus, deficit and mismatch) between the incubation process and the opportunity attributes of individual ventures, which directly influence venture performance (high, moderate and low). In turn, an incubator's performance is largely shaped by the overall performance of ventures in its portfolio.

This paper responds to the call for theory-building that links the antecedents and outcomes of the incubation process across levels of analysis. In addition to developing a conceptual model and research agenda at the intersection of entrepreneurship and business incubation, the proposed model also has implications for incubator directors deciding how to allocate limited resources, and for public/private sector administrators interested in leveraging investment in business incubators.

Looks at Arrow’s early background in New York and his subsequent development in the field of econometrics and mathematical economics. Covers his work in depth and his achievements in the school of thought of economics, adding that the modern school of thought is complementary to the classical school.

This paper aims to introduce the experience-dominant (Ex-D) logic model, which synthesizes the creation, perceptions and outcomes of Ex-D logic. It is designed to offer valuable insights for strategic managerial applications and future research directions.

Employing a qualitative approach by using eight selected product launch events from reviewed 100 event videos and 55 in-depth interviews with industrial managers to develop an Ex-D logic model, and data were coded and analysed via NVivo.

Results show that the firm’s Ex-D logic is operationalized as the mentalizing of the three types of customer needs (service competence, hedonic excitations and meaning making), the materializing of three types of customer experiences and customer journeys (service experience, hedonic experience and brand experience) and the moderating of three types of customer values (service values, hedonic values and brand values).

This study has implications for adding new insights into existing theory on dominant logic and customer experience management and also offers actionable recommendations for managerial applications.

This study sheds light on the importance of Ex-D logic from a strategic point of view and provides an organic view of the firm. It distinguishes firm perspective from customer perspective, firm experience from customer experience and firm journey from consumer journey.