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This paper aims to understand the most efficient hotel system and why efficiency varies across years and between the two differing types of hotel businesses in Turkey.

A data envelopment analysis (DEA) analysis was used to characterise the efficiency of all-inclusive (AI) and bed and breakfast (B&B) hotel businesses with one output (total revenue) and three inputs (labour, food and capital costs). The Malmquist approach is then used to discern changes in total efficiency (TTE) and intertemporal shifts in the efficiency frontier (technological change (Tch)).

The results reveal that the AI hotel operates at 100% efficiency in the summer and year-round. The B&B hotel business operates at 89.6% with variable constant returns to scale during the summer and with 100% efficiency. The results of the Malmquist approach indicate that the total factor productivity grew in the years 2015, 2016, 2018 and 2019, while the other years were marked by inefficiency. Such increases were due to technical efficiency change (TEch) and Tch, which means that managerial and allocative efficiency (AE) were barely achieved. Slight differences were noted in the two time periods (all year and summer), suggesting that the scale of hotel businesses is prepared to operate all year round, and this calls for strategies to mitigate seasonality.

As to avenues for future research, the limitations of this study are threefold. First, the hotel businesses are not parallel in terms of the duration of their service offerings. Future research may consider including an AI hotel business that is in operation for the whole year. Second, businesses in Turkey are sceptical about sharing their data as it is considered confidential. However, to better generalise the results and encourage hoteliers to consider the positive outcomes of such analysis, the number of observations could be increased by considering more hotel businesses in both categories. Third, a mixture of data representing businesses operating in various countries may reflect if the efficiency scores vary internationally.

Overall, AI hotel businesses are more attractive but less efficient than B&B. Furthermore, the external crisis impacts the efficiency of hotel businesses meaning that hotel managers could keep on exploring AI, perhaps educating their hosts not to waste or not offer huge quantities. Hotel managers may also need to enlarge their seasonal activities to ensure more efficiency.

Despite the intentions of AI hotel businesses to increase their profitability with a lower level of service quality, this study shows that the AI hotel business is very attractive but not so efficient due to the higher propensity of guests to consume food and beverages in excess that compromises the definition of efficiency as zero waste. AI is very attractive for family groups or those seeking the pleasure of relaxation at seaside resorts and is also very popular in Turkey. On the other hand, the B&B hotel business is more efficient but less attractive.

The contributions of this paper are threefold. First, the authors analysed the efficiency and inefficiency of hotel businesses within nine years of operations. During this period, Turkey experienced first a tourism boom (2011–2014) followed by stagnation and subsequently a sharp decline due to political instability resulting in an (in)direct impact on tourism (2015–2019). Second, the authors compared the efficiency and inefficiency of AI and B&B hotel businesses. Third, the authors examined the effects of hotel management factors to ensure efficiency.

The purpose of this paper is to contribute to the knowledge on the efficiency of the incubators in Mexico, from a double-managerial approach (incubator and start-ups) measuring the efficiency oriented to the survival growth in the employment.

The efficiency of 25 business incubators of a university in a Mexico was analyzed from 2012 to 2014. Through the envelope data analysis (DEA) technique, composed of five inputs and three outputs, which help to determine the decision-making units (DMUs) that are in the best practice border, being able to know the factors relevant and how they have been managed in the different incubators.

One of the three years observed was identified as the most efficient, with 13 start-ups at the most efficient border. The projection shows some entries that must be modified to maximize the creation of new incubated business with a focus on survival and growth. The authors propose the resources that must be modified to adopt efficient management practices for incubators and start-ups small size.

This analysis recognizes the size and restriction of resources as a determinant in the efficiency of intermediate technology business incubators. However, an obvious limitation is the non-standardized sample of 25 incubators does not allow generalizing the results.

The special support received by start-ups linked to a university with strong financial and non-financial support.

Dual management (incubator and incubated start-ups) approach to efficiency analysis and the use of the DEA for the incubation topic and to fill a gap persists in the understanding of creation of new business in intermediate technology.

As evident from the literature review, the research on cyber security performance is centered on security metrics, maturity models, etc. Essentially, all these are helpful for evaluating the efficiency of cyber security organization but what matters is how the factors of internal efficiency affect the business performance, i.e. the external effectiveness. The purpose of this research paper is to derive the factors of internal efficiency and external effectiveness of cyber security and develop impact model to identify the most and least preferred parameters of internal efficiency with respect to all the parameters of external effectiveness.

There are two objectives for this research: Deriving the factors of internal efficiency and external effectiveness of cyber security; Developing a model to identify the impact of internal efficiency factors on the external effectiveness of cyber security since there is not much evidence of research in defining the factors of internal efficiency and external effectiveness of cyber security, the authors have chosen grounded theory methodology (GTM) to derive the parameters. In this study emic approach of GTM is followed and an algorithm is developed for administering the grounded theory research process. For the second research objective survey methodology and rank order was used to formulate the impact model. Two different samples and questionnaires were designed for each of the objectives.

For the objective 1, 11 factors of efficiency and 10 factors of effectiveness were derived. These are used as independent and dependent variable respectively in the later part of the research for the second objective. For the objective 2 the impact models among independent and dependent variables were formulated to find out the following. Most and least preferred parameters lead to internal efficiency of cyber security organization to identify the most and least preferred parameters of internal efficiency with respect to all the parameters external effectiveness.

The factors of internal efficiency and external effectiveness constructed by using grounded theory cannot remain constant in the long run, because of dynamism of the domain itself. Over and above this, there are inherent limitations of the tools like grounded theory, used in the research. Few important limitations of GTM are as below in grounded theory, it is comparatively difficult to maintain and demonstrate the rigors of research discipline. The sheer volume of data makes the analysis and interpretation complex, and lengthy time consuming. The researchers’ presence during data gathering, which is often unavoidable and desirable too in qualitative research, may affect the subjects’ responses. The subjectivity of the data leads to difficulties in establishing reliability and validity of approaches and information. It is difficult to detect or to prevent researcher-induced bias.

The internal efficiency and external effectiveness factors of cyber security can be further correlated by the future researchers to understand the correlations among all the factors and predict cyber security performance. The grounded theory algorithm developed by us can be further used for qualitative research for deriving theory through abstractions in the areas where there is no sufficient availability of data. Practitioners of cyber security can use this research to focus on relevant areas depending on their respective business objective/requirements. The models developed by us can be used by the future researchers to for various sectoral validations and correlations.

Though the financial costs of a cyber-attack are steep, the social impact of cyber security failures is less readily apparent but can cause lasting damage to customers, employees and the company. Therefore, it is always important to be mindful of how the impact of cyber security affects society as well as the bottom line when they are calculating the potential impact of a breach. Underestimating either impact can destroy a brand. The factor of internal efficiency and external effectiveness derived by us will help stakeholder in focusing on relevant area depending on their business. The impact model developed in this research is very useful for focusing a particular business requirement and accordingly tune the efficiency factor.

During literature study the authors did not find any evidence of application of grounded theory approach in cyber security research. While the authors were exploring research literature to find out some insight into the factor of internal efficiency and external effectiveness of cyber security, the authors did not find concrete and objective research on this. This motivated us to use grounded theory to derive these factors. This, in the authors’ opinion is one of the pioneering and unique contribution to the research as to the authors’ knowledge no researchers have ever tried to use this methodology for the stated purpose and cyber security domain in general. In this process the authors have also developed an algorithm for administering GTM. Further developing impact models using factors of internal efficiency and external effectiveness has lots of managerial and practical implication.

The purpose of this paper is to investigate how new technology-based firms (NTBFs) overcome established notions of scale and scope through business model innovation, leveraging the value from digitalization.

The study adopts an exploratory research design, drawing on a novel data set of 50 publicly available interviews with vertical farming (VF) industry leaders and insiders who represent 36 different organizations from North America and Europe.

The study develops a framework showing how NTBFs leverage the value from digitalization via a paradoxical approach combining both efficiency and novelty value drivers.

The study extends current theorizing on the desirability of a combined business model approach leveraging both efficiency and novelty from digitalization. Furthermore, the study is among the first to investigate the unique and highly technological context of VF.

In this study, the impact of owner-operator and non-owner operator rice mills on productive efficiency is investigated.

Primary data collected from a survey of 111 rice mills in the Mwea region of Kenya are used. A metafrontier approach is employed to measure overall technical efficiency which is decomposed into managerial and organisational efficiency.

The results reveal no significant difference in overall technical and managerial efficiency between owner and non-owner operated mills. However, a significant difference exists in organisational efficiency of mills: non-owner operated mills were found to be performing significantly better than owner-operated.

The authors provide supporting evidence to the study and discuss some of the significant policy implications stemming from the study.

It is recognised that for owners to take the risk of divesting control to a hired manager rather than manage the firm themselves can have major strategic, financial and often emotional consequences. However, there is little empirical evidence on how production efficiency will develop as a result of hiring a manager with the underlying economic theory providing ambiguous guidance. Standard economic theory assumes that firms behave as profit maximisers, which can be achieved by operating efficiently. However, this may not always be the case and as the literature indicates, this may especially be so for small businesses in low- and middle-income countries.

The purpose of this paper is to analyse the direct impacts on financial performance and the added value of production in family businesses, considering the efficiency of intellectual capital as determining variables.

A comparative analysis between family businesses (FB) and non-family businesses (NFB) is proposed to explore significant differences in the impacts on financial performance and added value of companies, through multivariate techniques. It contributes to the literature on the family business, and its performance from an analytical framework that incorporates the theory of intellectual capital and the measurement of its impact.

The findings show that the value-added coefficient of intellectual capital (VAICTM) is a determining factor in the financial performance of companies and, to a greater extent, in the FB than in their NFB counterparts. It is also verified that the efficiency of intellectual capital in the FB has a direct and greater relationship with the value added of production (VAEmp), with respect to non-family businesses, being an important factor in predicting the performance of companies.

The findings allow us to conclude the importance of efficient management of intangible factors in companies, such as intellectual capital, becoming a competitive advantage factor.

The document explores the relationship and impact of VAICTM in family businesses that belong to an emerging economy and demonstrates the existence of differences between FB and NFB, at the level of intangible factors under a comparative analysis.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

As family and nonfamily businesses differ in how they do business, the focus of this manuscript is on understanding how strategy-level models can be misinterpreted if family involvement is not considered. Thus, in this manuscript, the focus is on understanding the extent to which strategic orientations (market orientation and technology orientation, which reflect strategic approach), strategic performance metric focus (financial-based, optimization-based and market-based, which reflect strategy evaluations) and strategic audacity (which reflects boldness in envisioning and delivering strategic outcomes) play a role in driving firm performance – in family businesses vs nonfamily businesses. Understanding how these drivers impact performance differently in family vs nonfamily businesses enables companies to better direct their strategic efforts.

After presenting theoretical concepts, authors use regression analysis on a sample of companies in a developing European Union (EU) country (n = 282) to evaluate the impact of strategic orientation, strategic performance metric focus and strategic audacity on firm performance separately in three samples: the full sample (consisting of both family and nonfamily-owned firms), sample of family businesses and the sample of nonfamily businesses.

The role of strategic orientation, strategic audacity and focal goals in driving firm performance differs depending on the company type (family vs nonfamily). In the case of nonfamily businesses, strategic audacity and technology orientation with the focus on efficiencies and markets are driving firm performance. In the case of family businesses, both market and technology orientation are important drivers of performance; the focus on financial and market indicators of performance is positively impacting performance, while the focus on efficiency indicators is diminishing the performance of family businesses. Thus, results show that of the performance drivers for family businesses, some are insignificant (strategic audacity), while some even have a negative impact (focus on optimization-based measures of performance) on family businesses' performance. Moreover, results show that some of the drivers of performance in case of family businesses (market orientation and focus on financial-based measures of performance) are not drivers of outstanding performance in the case of nonfamily businesses.

Best practices differ for family vs nonfamily businesses. In case of family businesses, comparing them to nonfamily businesses, market orientation and the focus on financial-based measures of performance have a greater impact on firm performance, while, at the same time, family businesses should refrain focusing on pursuing optimization-based measures of performance as such pursuit drives down their performance. Understanding the drivers of performance specific to family businesses will enable such firms to better navigate contexts characterized by ambiguity and uncertainty.

The manuscript evaluates how models, generally researched in the overall firm metrics, differ between family businesses and nonfamily businesses, thus delivering new insights into the important marketing concepts.

The purpose of this paper is to demonstrate the relevance of business intelligence (BI) in businesses in general and tourism firms in particular. BI has been hailed as an innovation that can propel businesses that adopt the system to high productivity and efficiency. This paper confirms that view but further adds that BI also enhances a business’s competitiveness.

This paper reviews literature on the use of BI in tourism. Although current literature is largely fragmented, focusing on BI, the tourism industry and the notion of competitiveness separately, this paper makes an attempt to bring the three sub-themes in the same study and highlights their interconnectedness. The study adopts two environmental analysis models to better analyze this matter. First is the environmental analysis model as based on Downes’s modification of Porter’s five forces framework. The second model used is the resource-based view approach to business environmental analysis.

This paper affirms that the tourism industry is one of those industries that continue to benefit from the advantages that come with the adoption of a BI system. Literature shows that the tourism industry was one of those that first adopted BI in order to benefit from the benefits that come with its adoption. Such advantages include flexible and user friendly tourists’ data capture, storage, retrieval, processing and analytical capabilities.

This was a largely literature review-based study. There is, therefore, room for strengthening its findings by conducting field work and mixed methods research for more robust results.

This study will surely benefit the tourism industry and business in general from its highly favorable conclusions to the benefits that come with the adoption of a BI system. It can also be used as a reference in to the tourism field, especially aggregating important concepts and literature that can help future practical studies.

Society will also benefit from this study in terms of the new knowledge that has been generated. Members of society will then be in a position to demand products and services that are a result of innovation and informed decision making.

Although this paper is largely based on literature, the conclusions reached are those of the authors. A close assessment of the literature in BI and the tourism industry was done, resulting in the conclusions reached by the authors.