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The purpose of this paper is to suggest a framework for extracting the sequential patterns of maintenance activities and related spare parts information from historical records of maintenance data with pre-defined support or threshold values.

A data mining approach has been adopted for predicting the maintenance activity along with spare parts. It starts with a collection of spare parts and maintenance data, and then the development of sequential patterns followed by formation of frequent spare part groups, and finally, integration of sequential maintenance activities with the associated spare parts.

This study suggests a framework for extracting the sequential patterns of maintenance activities from historical records of maintenance data with pre-defined support or threshold values. A rule-based approach is proposed in this paper to predict the occurrence of next maintenance activity along with the information of spare parts consumption for that maintenance activity.

Presented model can be extended for analyzing the failure maintenance activities and performing root cause analysis that can give more valuable suggestion to maintenance managers to take corrective actions prior to next occurrence of failures. In addition, the timestamp information can be utilized to prioritize the maintenance activity that is ignored in this study.

The proposed model has a high potential for industrial applications and is validated through a case study. The study suggests that the model gives a better approach for selecting spare parts based on their similarity or correlation, considering their actual occurrence during maintenance activities. Apart from this, the clustering of spare parts also trains maintenance manager to learn about the dependency among the spares for group stocking and maintaining the parts availability during maintenance activities.

This study has used the technique of data mining to find dependent spare parts itemset from the database of the company and developed the model for associated spare parts requirement for subsequent maintenance activity.

The purpose of this paper is to explore self-management among informal tourism employees in urban China with the theoretical basis of Jianghu and reveal the forming process and operation mechanism of China’s urban informal organizations’ self-management.

This paper adopts process–event analysis of informal tourism photographers surrounding Guangzhou Tower. Conducting field inspection and in-depth interviews, the forming process is analyzed and typical events are captured to unveil this self-management mechanism.

The self-management of informal tourism employees in China is based on the Jianghu theory, which specifies the role, obligation and responsibility of a member. These above rely on word-of-mouth order or implicit ways to treat newcomers, realize internal communication and deal with public affairs. Brotherhood, benevolence and etiquette make up the core values of the Jianghu theory that advises strategies in dealing with different events. This self-management, based on the Jianghu theory, has not only effectively solved internal conflicts, but has also achieved the goal of social management.

Informal employees’ self-management is extremely important due to the high cost of government intervention. Through China’s urban informal tourism employees’ Jianghu-styled self-management, the paper shows that the government should not crack down on this group indiscriminately. Instead, it should, through the management agent, set up effective Jianghu rules to realize regular control over this group.

This article aims at investigating knowledge transfer and exchange (KTE) between founder firms and corporate foundations (CFs), looking at mechanisms able to enhance CFs’ orientation of effectiveness.

We analyze 50 questionnaires collected through a survey of CFs based in Italy (redemption of 42.7% of the total). We use a number of regressions to verify the change of explained variance moving from a basic model with control variables (enter method) and a model including KTE mechanisms with an impact on orientation to effectiveness (stepwise method).

The analysis produced a model which underlines the influence of knowledge transfer mechanisms in stimulating orientation to effectiveness. The adoption of specific knowledge transfer mechanisms by founder firms can have a significant influence on how CFs manage their effectiveness. Three mechanisms emerge from the study as elements with a positive impact.

The results apply to nonprofit or public bodies, especially if we consider partnerships or organizational networks. The individuated criteria for selecting a positive KTE could drive similar choices of other nonprofit bodies.

The study individuates a set of practices that are potentially able to influence positively the orientation to effectiveness of CFs, and the capacity to perform their activities and respond to social needs more successfully.

This research considers CFs as founder firms’ subsidiaries, with a growing strategic importance. This research reveals how KTE mechanisms can foster the development of orientation to effectiveness if implying interaction, firms’ commitment, autonomy, and alignment with the firms’ strategy and CFs’ purposes.

City logistics is a challenge in many cities. Literature works focus on the analysis of large or local-scale solutions to increase the efficiency of freight transport. However, store deliveries from the perspective of practitioners, particularly retail stores, are still an issue. In this context, the purpose of this paper is to propose a decision framework to assist logistics managers in defining efficient re-shelving solutions for store deliveries, according to the emplacement characteristics, city administration constraints and social issues.

An iterative step-by-step decision framework is developed, which allows taking decisions in a clear and structured way, including the preferences of key stakeholders. Moreover, a “what if” procedure is proposed, aiming to modify some initial conditions of the target store to achieve more efficient solutions.

The proposed decision framework is applicable in practice and helps users (mainly logistics managers) to identify solutions for efficient re-shelving in urban settings.

The decision framework is applied by the logistics manager of two Spanish food retail stores, but it could be used in different logistics sectors and cities/regions, although adapting the decisions taken at each phase.

Logistics managers have a support tool when addressing re-shelving solutions for store deliveries.

A balance can be found between company interests (minimise costs) and citizens quality of life (less contamination, noise, traffic, etc.).

This study simultaneously deals with large- and local-scale decisions faced by logistics managers in their day-to-day activity, considering details about the store location, its surroundings and the company it belongs.

This study aims to investigate marketing managers’ views on the existence and nature of the academic–practitioner gap in the branding domain.

Using a purposive sampling method, the researchers conduct semi-structured qualitative interviews with 20 experienced marketing managers from a wide range of industries and organisations, whose roles are focussed on the planning, implementation and management of broad marketing and branding strategies.

Branding practitioners have little or no contact with academics and their theories-in-use with regard to brand management suggest they do not consider academic research relevant to their work.

The process of describing and explaining the gap provides valuable insights into bridging the gap; it provides actionable branding strategies that include raising awareness, building relationships, improving the benefits offer and communicating more effectively.

This research has practical implications for branding academics. The interviewed practitioners confirm the gap, viewing it as academics’ (not practitioners’) problem and responsibility. They characterise it as a branding problem that academics can overcome using branding strategies, to establish themselves as credible sources of branding expertise for practitioners. Key areas for increasing collaboration stem from practitioners’ desire for independent, credible, ethical and timely third-party advice on branding issues; relevant, timely and shorter professional branding education across their organisations; and closer connections with universities to identify new branding talent and ideas.

To the best of the authors’ knowledge, this paper is the first to empirically examine and recommend solutions to the academic-practitioner gap in the branding domain by studying marketing professionals with branding responsibilities, using in-depth interviews.

Greening existing buildings (GEB) considerably improves energy efficiency of old buildings, along with other benefits, but it is not widely practiced. As a part of a wider study, this paper aims to evaluate the perception of building dwellers/owners on the challenges and motivators to GEB in Brunei Darussalam.

A structured questionnaire survey collected 109 responses from building owners/dwellers. Cronbach's alpha tested the reliability of the data collected. One-sample t-test examined if sample means are consistent with population means. ANOVA examined if different respondent groups significantly agreed on the importance levels of individual factors. Moreover, factor analysis narrowed down the long list of factors in to a smaller number of components.

A set of 30 challenges and 19 motivators of GEB was identified. “Lack of a GEB infrastructure” was identified as the collective key challenge, leading dwellers to recognize lack of support and knowledge and develop wrong perception on GEB. However, “framework of supports,” as a summative motivator, improves knowledge and awareness on GEB, which allows recognizing other benefits and developing a momentum of practicing GEB. Factor analysis suggested a consolidated approach for challenges through six interrelated components, but for motivators to focus on somewhat four independent areas.

House/building dweller/owners' decision is the key to undertake GEB. This study, apparently for the first time, contributes to identifying the challenges and motivators that influence their decision-making.

The main purpose of this study is to forecast inflation rates in the case of the Turkish economy with shrinkage methods of machine learning algorithms.

This paper compares the predictive ability of a set of machine learning techniques (ridge, lasso, ada lasso and elastic net) and a group of benchmark specifications (autoregressive integrated moving average (ARIMA) and multivariate vector autoregression (VAR) models) on the extensive dataset.

Results suggest that shrinkage methods perform better for variable selection. It is also seen that lasso and elastic net algorithms outperform conventional econometric methods in the case of Turkish inflation. These algorithms choose the energy production variables, construction-sector measure, reel effective exchange rate and money market indicators as the most relevant variables for inflation forecasting.

Turkish economy that is a typical emerging country has experienced two digit and high volatile inflation regime starting with the year 2017. This study contributes to the literature by introducing the machine learning techniques to forecast inflation in the Turkish economy. The study also compares the relative performance of machine learning techniques and different conventional methods to predict inflation in the Turkish economy and provide the empirical methodology offering the best predictive performance among their counterparts.

The purpose of this paper is to examine information-seeking behavior (ISB) of strategic planners in enterprise across different work-task types and stages.

A case study was conducted in a pharmaceutical company in China, labeled as T Company. One of the authors worked in the department of strategic planning of this company as an intern. The data were collected via participant observation and unstructured in-depth interviews. Open coding was performed to analyze the data.

Four work-task stages were identified: project preparation, gathering, discovery and presentation, and strategy formulation. The results indicate that work-task types, work-task stages, and strategic planners’ work role or position affect their information needs, source selection, and seeking process. Task complexity, task familiarity, and task goal are of the most important task attributes that directly shape strategic planners’ ISB. Work role determines the extent to which strategic planners can access the information of the company. Internal information has priority, but external information is also important when internal information is not sufficient; both are equally important for strategic planning projects. Social media has been a very important channel to access, disseminate and share information. Workshops are an important approach to producing final project reports. Face-to-face discussion and information exchange play a critical role in the formulation of new strategies.

This is a case study with data collected from only one company in China. Some of the results may not be generalizable. However, it adds new knowledge to ISB research in enterprise, informs people how to provide better information services for strategic planners, and informs MBA education for students’ better information-seeking skills.

Though myriad studies on ISB, little research has been done to examine strategic planners’ ISB from a business context, especially taking into account the effect of work-task types and stages.

The purpose of this paper is twofold. First, the authors investigate the main drivers of house prices in the Hong Kong housing market. Second, further research is undertaken to confirm the existence of house price overvaluation, which has driven the market into a bubble episode.

First, the authors propose a theoretical framework to identify the fundamentals of the market. In the second step, they decompose house prices into fundamentals, frictions and bubble episodes for a better understanding of the evolution of house prices during the period 1996(Q3)-2013(Q3).

The results of this paper suggest an eventual possible correction of up to 46 per cent of house prices with respect to their 2013(Q3) level.

The originality of this paper is to use the procedure developed by Glindro and Delloro (2010) to analyse the Hong Kong housing market. The contribution of this paper also modifies the original Glindro and Delloro’s (2010) approach by including the Christiano and Fitzgerald (2003) filter to decompose house prices.

The purpose of this study is to make an analysis of the short- and long-term effects of inflation, exchange rate, housing interest rate, industrial production index, total housing loans and housing volume on housing inflation in Turkey, taking into account the multiple structural breaks.

Multiple structural break Lee–Strazicich unit root test, autoregressive distributed lag bound test and Granger causality test based on error correction model were used.

There is both a short- and long-term relationship between housing prices and macrovariables. Housing prices are mostly affected by housing interest rates, housing volume, real exchange rate and total housing loans in the short run. In the long run, it is mostly affected by total housing loans, housing volume and housing interest rates.

The variables used in the analysis are: housing price index, consumer price index, dollar rate, housing interest rate, industrial production index, total housing loan amount and domestic loan volume. Because the data that variables started common is 2010:M01, the period starting from this date until 2021:M12 is considered. The research covers only Turkey as a country. Determining the micro- and macroeffects of housing prices can always offer solutions for the problems experienced in housing supply and housing demand.

While investigating housing prices, there are no studies in which total housing loans and housing volume are included in the model together. However, it is important to analyze the effect of the current conjuncture, in which there has been constant increases in foreign exchange rates and high inflation in recent years, on housing prices in Turkey. In this study, investigating these effects by using econometric methods that include structural breaks also increases the original value of this study.