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The purpose of this paper is to suggest ways that we can widen our vision since our views are limited by our theoretical lens.

The paper first draws on articles in the current issue to illustrate how limitations imposed by our theoretical lens can be partly overcome. It then draws on the insights from two recent papers by Svensson (2016) and Lo and Chik (2016) to discuss some ways forward. Svensson’s paper argues for integrating research on teaching and learning using case-based studies and the contextual analysis approach. Lo and Chik’s paper is about how our learning can go beyond the single case through attending to fusion in the external horizon. The conceptual lens from these two papers which are from the phenomenography, variation theory and learning study tradition is applied to look at some of the papers in this issue which are from the lesson study tradition.

Although there is an inherent limitation to what we can see as a consequence of the theoretical lens that we take, we can widen our vision by learning to see from others’ perspectives and gain insights that would be useful to us.

The conceptual lenses from the phenomenography, variation theory and learning study tradition is applied to look at some of the papers which are from the lesson study tradition to reveal alternative ways of seeing.

This paper aims to design an algorithm which is used to deal with non-linear discrete systems with constraints under the lower computation burden. As a result, we solve the non-holonomic vehicle tracking problem with the lower computational load and the convergence performance.

A fusion event-triggered model predictive control version is developed in this paper. The authors designed a shrinking prediction strategy.

The fusion event-triggered model predictive control scheme combines the strong points of event triggered and self-triggered methods. As the practical state approaches the terminal set, the computational complexity of optimal control problem (OCP) decreases.

The proposed strategy has proven to stabilize the system and also guarantee a reproducible solution for the OCP. Also, it is proved to be effected by the performance of the simulation results.

The purpose of this paper is to explore the application of a hermeneutic-based approach as innovative way to study the Cultural Heritage management in a mesoeconomic space.

The paper builds a theoretical framework based on the analysis of relevant literature in the field of cultural economics, heritage economics and conservation and restoration techniques. Then, after having defined the conceptual hypothesis, a hermeneutical interpretative model is designed for the analysis of the processes of Cultural Heritage management with particular regard to the strategies of stakeholder engagement.

The research shows how the mesoeconomic space is that border area where it is possible to solve more easily the conflicts that arise as a result of the different expectations of stakeholders. Hermeneutical analysis, applied in iterative form, allows us to find common connections, points of contact and convergences between the interpretative horizons of the various stakeholders.

The application of the interpretative model allows the identification of the expectations of stakeholders, improving the knowledge of the tangible and intangible attributes of works of art, in order to design appropriate interventions of restoration, conservation and valorization.

The new model of analysis, based on hermeneutic methodology, is designed to understand and describe the social and economic relations between the different stakeholders involved in the management of Cultural Heritage.

This paper examines for the first time the Cultural Heritage sector within the mesoeconomic area between the micro and the macroeconomy. In addition to this mesoeconomic analysis and conceptual approach, the authors introduce as methodology the economic hermeneutics that represents an innovative tool in the field of economic and business disciplines.

In this paper I argue that the liberal problem of religion, which defines religion in terms of dogmatism or opaque justifications based on ‘revealed truth’, needs to be rethought as part of a broader problem of dialogue, which does not define religion as uniquely problematic.

Habermas argues for religious positions to be translated into ‘generally accessible language’ to incorporate religious citizens into democratic dialogue and resist the domination of instrumental rationality by enhancing ‘solidarity’. I contrast this with Rowan Williams’ and Gadamer’s work.

Williams conceptualises religion in terms of recognising the finitude of our being, rather than dogmatism or opacity. This recognition, he argues, allows people to transcend the ‘imaginative bereavement’ of seeing others as means. Using Williams, I argue that Habermas misdefines religion, and reinforces the domination of instrumental rationality by treating religion as a means. I then use Gadamer to argue that the points Williams makes about religion can apply to secular positions too by recognising them as traditions subject to finitude.

This is original because it argues that the liberal problem of religion misdefines both religion and secular positions, by not recognising that both are traditions defined by finitude. To reach, dialogically, a ‘fusion of horizons’, where religious and secular people are understood non-instrumentally in their own terms of reference, will take time and not trade on immediately manifest – ‘generally accessible’ – meanings.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

The purpose of this paper is to develop an innovative branding method based on the hermeneutical approach and interpretive theory, to respond to the need of a simple and effective tool to build corporate identity through an industrial brand identity design and, being a new business, has been considered the brand perception of their stakeholders as the main input to analyze.

The case study of a small- and medium-sized enterprise (SME), that produces nanomaterials for the business-to-business (B2B) industrial market, is used to design the new hermeneutic branding method. The methodology process has been structured in four phases that have marked the investigation and that correspond to four different levels of knowledge that, in succession, between them, constituted the so-called hermeneutic circle.

This new approach allowed us to understand the social phenomenon related to the brand: its characteristic, context and the brand itself. Though hermeneutic analysis has confirmed that business strategy is only part of a more complex system of brand management, it must also consider the competitive environment and the views of the stakeholders.

This paper contributes to research on industrial branding by adopting the hermeneutical approach in managerial practice. This paper is the first of its kind in detail modelling the design phases of a B2B brand, providing an operational tool for marketing specialists.

There is a lack of research studies in the methods for designing industrial brands. The contribution of this paper lies in proposing a new interpretative approach that, acknowledging the different expectations of the stakeholder in the supply chain, allows to draw a B2B brand that communicates the system values of the product and company.

Trading on electricity markets occurs such that the price settlement takes place before delivery, often day-ahead. In practice, these prices are highly volatile as they largely depend upon a range of variables such as electricity demand and the feed-in from renewable energy sources. Hence, the purpose of this paper is to provide accurate forecasts..

This paper aims at comparing different predictors stemming from supply-side (solar and wind power generation), demand-side, fuel-related and economic influences. For this reason, this paper implements a broad range of non-linear models from machine learning and draw upon the information-fusion-based sensitivity analysis.

This study disentangles the respective relevance of each predictor. This study shows that external predictors altogether decrease root mean squared errors by up to 21.96%. A Diebold-Mariano test statistically proves that the forecasting accuracy of the proposed machine learning models is superior.

The performance gain from including more predictors might be larger than from a better model. Future research should place attention on expanding the data basis in electricity price forecasting.

When developing pricing models, practitioners can achieve reasonable performance with a simple model (e.g. seasonal-autoregressive moving-average) that is built upon a wide range of predictors.

The benefit of adding further predictors has only recently received traction; however, little is known about how the individual variables contribute to improving forecasts in machine learning.

Organizations are consistently seeking innovative strategies and novel pathways to enhance business processes and create differentiation. The global business ecosystem is changing and there is growing demand for multi-modal digital technologies, big data consolidation and data analytics to harness a cost-competitive agile system. Technological convergence and integration of digital systems is one of the preferred methodologies that facilitates new and effective workflows and revives business processes. The progressive interlinking of digital technologies with business operations leads to the convergence and blending of management disciplines, devices and applications. The growing inconsistencies in managerial understanding regarding the benefits of convergence prompts a comprehensive examination of digital convergence pathways, identifying the impacts on converging entities and business objectives. The State bank of India (SBI) mega-merger case study was selected to investigate the pragmatic framework of digital convergence and to understand the impacts on interlinked entities such as: business operations, strategic management, project team that support value creation and competitive differentiation. The purpose of this paper is to focus on the phenomena of techno-fusion of emerging technologies creating new opportunities, business models and unique strategies for global banking and financial service organizations.

This study applies the qualitative, inductive research method using critical reflection of before and after the implementation of convergence and digital integration strategies. The SBI case study employs this research strategy based on the premise that banks must stay agile and highly responsive to the changing environment to enhance its value proposition and competitive differentiation objectives. The study methodology incorporates cooperative inquiry and multiple levels of analysis using data collection techniques of exhaustive review of archives, informal interviews, questionnaires and observations to identify the synergistic process improvement pathway. The study is grounded on the concept that the convergence of diverse business pathways involves innovative and interlinked project, strategic and information technology (IT) workflows that results in open innovative systems.

The studies identify that organizational innovation and creative solutions are a result of ecosystem turbulence, environmental force diversity, competitive pressure and the need for differentiation. Organizations that harness the power of digital fusion and convergence of management, systems and data generate a competitive advantage. The technological convergence strategy pulls multiple business and technology processes (project, strategic, IT, Cloud, AI and business process management) at the organizational, divisional or functional level generating new opportunities and threats, new business models and unique growth strategies for global banking and financial services organizations. Organizations that fully integrate techno-fusion of business and digital strategies produce synergistic effects and enhance adaptability, innovation and resiliency in the face of competitive challenges.

Additional areas that can be explored further as an extension of this study are listed below: identifying factors to improve the speed of convergence; the current results are limited to large size organizations where formal management and technology functions are distinctive. Similar studies on smaller organizations are warranted.

This study focuses on the evolving field of technology innovation, which is increasingly being intertwined with business operations. Innovative digital technology is enabling the convergence of the disciplines of management, digital devices and applications. This facilitates the creation of a pragmatic framework that supports convergence of business operations, strategic management and digital fusion which leads to value creation and competitive differentiation. The techno-fusion of emerging technologies and digital strategies generates new opportunities and threats, new business models and unique growth strategies for organizations.

Evolutionary developmental biology is a highly variable scientific innovation because researchers can adapt their involvement in the innovation to the opportunities provided by their environment. On the basis of comparative case studies in four countries, we link epistemic properties of research tasks to three types of necessary protected space, and identify the necessary and facilitating conditions for building them. We found that the variability of research tasks made contributing to evolutionary developmental biology possible under most sets of authority relations. However, even the least demanding research depends on its acceptance as legitimate innovation by the scientific community and of purely basic research by state policy and research organisations. The latter condition is shown to become precarious.