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The purpose of this paper is to present a community-led “informal heritage management” of the chini-tikri work of Kosaituli mosque, Old Dhaka, Bangladesh. It critically explores the interrelationship between the craft, existing social capital and informal heritage management.

This paper assesses the existing local policies, strategies and the top-down conservation efforts led by government and identifies the shortcomings. The study uses Kosaituli mosque as a case study as it displays some of the finest surviving examples of the chini-tikri work. Using observation, open-ended interview and focus group discussion as research tools, the study explores the challenges that the craft and craftsman faces, how existing social capital supports the informal heritage management process and the interrelationship between these critical elements.

The results shows two clear issues. First, the informal heritage management system has been continuing to protect and manage the local heritage while fighting several challenges. Second, though they require external support, they want to keep the “community ownership.” The study recommends how the craftsman can be revived through incentives and capacity building to facilitate the survival of the craft with a three-step process: identifying the rare craftsmen, providing them due recognition and transferring the traditional knowledge to the next generation.

No similar prior studies were carried out in Old Dhaka that focus on this subject. This paper can contribute in new policy formation not only for Bangladesh but also will potentially guide other cities that face similar challenges of disappearing craft and craftsman.

In order to more accurately predict the dynamics of the e-commerce market and increase the comprehensive value of the circular e-commerce industry, proposes to use Grey system theory to analyze the circular economy of the e-commerce market.

Construct a Grey system theory model, analyze the big data of e-commerce and circular economy of the e-commerce market and predict the development potential of China's e-commerce market.

The results show that the Grey system theory model can play an important role in the data analysis of circular economy of the e-commerce market.

Use Grey model to analyze e-commerce data, discover e-commerce market rules and problems and then optimize e-commerce market.

The purpose of this paper is to define new method (grey model (GM)) for predicting the value of gases in oil‐immersed power equipment, as well as change the traditional GM which requires equal interval data.

Trend forecasting is an important aspect in fault diagnosis and work state supervision, however, in practice, it is not practical that a number of data is necessary to build the forecast model. In transformer, the concentration of the gases dissolved in transformer oil is associated with gas type, oil quality, oil temperature, transformer load, etc. which some are known, others are unknown. So it can consider that transformer is grey system and the theory of grey system is chosen as a mathematical framework to solve the problem of forecasting the change of gases.

If possible, the results should be accompanied by significance.

Accessibility and availability of data are the main limitations which model will be applied.

A very useful advice for power transformer fault diagnosis method based on dissolved gas analysis data.

The paper presents a new approach of forecasting the value of gases in oil‐immersed power equipment and is aimed at unequal interval gases data which is used to GM.

Because of the high volatility with unstable data patterns in the real world, the ability of forecasting price indices is notoriously embarrassing and represents a major challenge with traditional time series mechanisms; especially, most of the traditional approaches are weak to forecast future predictions in the high volatile and unbalanced frameworks under the global and local financial depressions. The purpose of this paper is to propose a new statistical approach for portfolio selection and stock market forecasting to assist investors as well as stock brokers to predict the future behaviors.

This study mainly takes an attempt to understand the trends, behavioral patterns and predict the future estimations under the new proposed frame for the Colombo Stock Exchange (CSE), Sri Lanka. The methodology of this study is carried out under the two main phases. In the first phase, constructed a new portfolio mechanism based on k-means clustering. In the second stage, proposed a nonlinear forecasting methodology based on grey mechanism for forecasting stock market indices under the high-volatile fluctuations. The autoregressive integrated moving average (ARIMA) predictions are used as comparison mode.

Initially, the k-mean clustering was applied to pick out the profitable sectors running under the CSE and results indicated that BFI is more significant than other 20 sectors. Second, the MAE, MAPE and MAD model comparison results clearly suggested that, the newly proposed nonlinear grey Bernoulli model (NGBM) is more appropriate than traditional ARIMA methods to forecast stock price indices under the non-stationary market conditions.

Because of the flexible nonlinear modeling capability, proposed novel concepts are more suitable for applying in various areas in the field of financial, economic, military, geological and agricultural systems for pattern recognition, classification, time series forecasting, etc.

For the large sample of data forecasting under the normality assumptions, the traditional time series methodologies are more suitable than grey methodologies. However, the NGBM is better both in model building and ex post testing stagers under the s-distributed data patterns with limited data forecastings.

The purpose of this paper is to unify the expression of fractional grey accumulating generation operator and the reducing generation operator, and build the FDGM(1,1) model with the unified fractional grey generation operator.

By systematically studying the properties of the fractional accumulating operator and the reducing operator, and analyzing the sensitivity of the order value, a unified expression of the fractional operators is given. The FDGM(1,1) model with the unified fractional grey generation operator is established. The relationship between the order value and the modeling error distribution is studied.

The expression of the fractional accumulating generation operator and the reducing generation operator can be unified to a simple expression. For −1<r < 1, the fractional grey generation operator satisfies the principle of new information priority. The DGM(1,1) model is a special case of the FDGM(1,1) model with r = 1.

The sensitivity of the unified operator is verified through random numerical simulation method, and the theoretical proof was not yet possible.

The FDGM(1,1) model has a higher modeling accuracy and modeling adaptability than the DGM(1,1) by optimizing the order.

The expression of the fractional accumulating generation operator and the reducing generation operator is firstly unified. The FDGM(1,1) model with the unified fractional grey generation operator is firstly established. The unification of the fractional accumulating operator and the reducing operator improved the theoretical basis of grey generation operator.

The purpose of this paper is to derive the analytical expression of fractional order reducing generation operator (or inverse accumulating generating operation) and study its properties.

This disaggregation method includes three main steps. First, by utilizing Gamma function expanded for integer factorial, this paper expands one order reducing generation operator into integer order reducing generation operator and fractional order reducing generation operator, and gives the analytical expression of fractional order reducing generation operator. Then, studies the commutative law and exponential law of fractional order reducing generation operator. Lastly, gives several examples of fractional order reducing generation operator and verifies the commutative law and exponential law of fractional order reducing generation operator.

The authors pull the analytical expression of fractional order reducing generation operator and verify that fractional order reducing generation operator satisfies commutative law and exponential law.

Expanding the reducing generation operator would help develop grey prediction model with fractional order operators and widen the application fields of grey prediction models.

The analytical expression of fractional order reducing generation operator, properties of commutative law and exponential law for fractional order reducing generation operator are first studied.

In practical engineering, there are various sequences. The purpose of this paper is to improve and put forward a new model.

Based on the generalized accumulated generating operation, the paper improved the GM(1,1) cosine model and proposed the GAGM(1,1) cosine model.

It is found that the GAGM(1,1) cosine model can satisfy many kinds of periodic sequences and the precision of GAGM(1,1) cosine model is higher than the GM(1,1) model.

The paper shows that the GAGM(1,1) cosine model has important theoretic and practical significance.

The purpose of this paper is to concern the use of analytics as a calculative engine enabling coordination and control for the development process in a creative digital business environment.

This research employs an explorative field study approach, using interview data from professionals working with free-to-play mobile game development. Drawing on the concepts of cycles of accumulation, accounting as an engine and mediating instruments, this study examines how organisational actors using the analytics in a digital business environment participate in the data generation that accumulates knowledge about and new insights into the desired outcome.

The real-time metrics provided the means for organisational actors to continually monitor, visualise and if necessary intervene in the creative “good game” development process. Timely quantification and visualisation of user actions, collected as digital traces, enhanced the cycle of information accumulation. This new knowledge resulted in a desire for improvement and perfection, which directed the actions towards the organisational objectives.

This study furthers our understanding of the performativity of accounting as an engine and the user behavioural data trace as its “fuel” in a digital product development. It highlights the role of analytics as a “fact-generating” device, capable of transforming the raw user behavioural data, the fuel, into powerful explanations through visualisations of ideals. The real-time metrics, understood as mediating instruments, enable the generation of new insights and accumulation of knowledge guiding the further development towards the desired outcome, the “good game”.

Refugee entrepreneurship is increasing because of the increased influx of refugees around the globe. This leaves us with the question that how refugees integrate economically in the host country in the presence of all social, emotional and economic constraints. Existing literature suggests looking into the role of social capital to address refugee economic integration, particularly in developing nations. To acknowledge this call, this paper aims to explore the impact of family social capital on the economic integration process. Particularly, this study has investigated the Afghan refugee entrepreneurial activities and the integration process of Afghan refugees in economic and social spaces in Pakistan.

The study is rooted in 18 in-depth interviews with five participants that run small businesses in the city of Rawalpindi in Pakistan.

The findings revealed Afghan refugee entrepreneurs, develop a different type of family social capital i.e. horizontal and vertical social capital. Afterward, when the acculturation pace up across refugees’ generations then they accumulate bridging social capital gradually. The process of economic integration happens in different stages as also shown in the existing literature. Based on (Berry, 2003; Evansluong et al., 2019; Khulman, 1991) economic integration process this paper has discussed three main stages (entry in labor market, gradual integration and gradual sub-merging in host society) of Afghan refugee economic integration in Pakistan and further this study has shown how different steps are arranged within these stages to smoothen the integration process.

With this research, this paper calls for a more nuanced approach to address the challenges that are faced by refugees during their economic integration. Future research on Afghan economic and social integration can contribute to a better understanding of refugee settlement, well-being and self-sufficient status in host countries. One of the limitations of the study is the focus on male participants because female Afghan refugees do not work mostly because of strong patriarchal structures observed in refugee Afghan groups.

Most Afghan entrepreneurs consider them as Pakistani and do not want to repatriate to Afghanistan. This provides an opportunity for Pakistani policymakers to provide regulations and opportunities to Afghan entrepreneurs who want to stay in Pakistan and contribute to their family well-being and economic income generation and employment in Pakistan.

The role of the family acts as a means to refugee entrepreneurs’ integration in the host country. Strong migration networks and dense family configurations are a source of pride, responsibility, resilience and self-esteem for Afghan refugees to start and expand their businesses.

This study provides the opportunity to explore the under-researched role of family social capital in the migrant and refugee entrepreneurship literature.