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Abstract

Small and medium-sized enterprises (SMEs) play important roles in driving domestic economy. The purpose of this research was to examine the causal relationship model among factors that influence on operational performance (OP) in real estate business (REB), Thailand. The 555 samples of REB entrepreneurs were randomly selected by the multi-stage sampling method. A questionnaire was employed as a research tool for collecting data and analyzed with the structural equation model (SEM). The generated model is fit (χ²/df = .835, p = .993, GFI = .960, AGFI = .945, CFI = 1.000, RMSEA = .000). Findings revealed statistically significant that market orientation (MO) has positively influenced on operational performance, innovativeness (IN) and learning orientation (LO) (p < 0.001). Learning orientation has positively affected to innovativeness (p < 0.05) but non-significant affected to operational performance (p > 0.05). Lastly, innovativeness has positively influenced on operational performance (p < 0.001). Additionally, learning orientation has mediated between market orientation and innovativeness. The antecedent factors (MO, IN and LO) have cooperatively explained the causal relationship model that influenced on operational performance at 62.80%. Therefore, entrepreneurs in REB are able to achieve strategically their operational performance by consideration and implementation in mainly of the activities related with market orientation and innovativeness.

Keywords

Market orientation learning orientation innovativeness operational performance real estate business

Introduction

There are many findings around the world found the beneficially economic significance of the small and medium-sized enterprises (SMEs) in which a main force to drive domestic circumstances. SMEs in European or other developed countries have powerfully driven economy of these countries and have played very important to employment and poverty problem alleviation.¹ SMEs are the units to create new jobs, employment, incomes, new concepts, and innovativeness for an organization of entrepreneurs.² In Thailand, the economic system mostly depends on exports of the secondary industries that they are in the strong infrastructures of whole industries, and the heart of them is SMEs. In addition, SMEs in Thailand has also taken evolution and development based on the nation plans and the world economy trends. However, social and economic issues have been rapidly changed with the intensive globalization. Therefore, Thai SMEs need to be emphasized and developed by both governmental and non-governmental agencies in order to become the robust SMEs and readiness to solve various problems and challenges.³

According to the study of Kruasom,⁴ the gross domestic product (GDP) in Thailand was driven by SMEs at 37.4% in 2016, and toward with information of the Office of SMEs Promotion, the GDP structures of SMEs in 2018 were found that the service sector was still the most important economy activity (44.0%), the trading sector (31.4%), and the manufacturing sector (24.6%), respectively. Moreover, following the discussion for the GDP growth rate of SMEs in 2018, there was found that the service sector took an average growth rate of 4.6% per year. Thus, trends of the service sector will be an important factor caused the GDP of SMEs to grow up in the future.⁵

Within SMEs roles in 2018, the service sector that had the highest GDP was the real estate business (REB) in which providing a total value of 930,260 million Baht. Moreover, there were the hotel and restaurant section with a total value of 733,637 million Baht and the transportation and communication section with a total value of 429,249 million Baht, respectively. In 2019, the real estate section has directly expanded with the 4.5% growth that was an interesting business and seen to be continuous growth.⁵

Interestingly, real estate business in Thailand is the one sector in which forcing the economic growth of Thailand even the economic circumstances have been affecting as uncontrollable factor. In definition for particular study, real estate business is defined as a business concerning buying and selling both of land and buildings. However, the transaction and authority of rights in these assets are upon the laws and recent regulations following the Department of Lands, Ministry of Interior. It means that, for example, a foreigner is not able to be the owner of land and buildings by 49% of rights. Each type of land and buildings is identified the fee rate differently.⁶ The asset value of real estate business that is huge or less, is variously depended on location, classification of rights, government projects and current market price. For instance, nearby the central of country, the market price is very expensive. Therefore, operational performance of real estate business should be investigated.

The empirical studies about SMEs operational performance around the world^7

–12 and in Thailand^13,14 have been tightly emphasizing into three essential aspects: market orientation, learning orientation, and innovativeness. Therefore, the study toward the service sector SMEs especially REB becomes the currently interesting issue in terms of such three aspects how to influence on operational performance of REB.

Literature review

For natures of SMEs and real estate business in Thailand, SMEs have mentioned to the groups of small and medium-sized enterprises emphasized on three main sectors; (1) the manufacturing sector comprises agricultural processing, production processing, and mining; (2) the trading sector comprises wholesale and retail; (3) the service sector comprises food and beverage services in hotels and restaurants, entertainment service, transportation and communication, real estate, and accommodation. SMEs scale is considered from the permanent asset value and number of the full-time employees. So that, the small-sized SMEs have no more than 50 million Baht of capital investment and no more than 50 employees, and the medium-sized SMEs take capital investment between 51 and 200 million Baht and have 51–200 employees.¹⁵

The real estate business in Thailand includes also all business transactions about land and buildings undertaken by the same SMEs regulations, taxes, laws, operational policies, and internal economy situations. Details of the real estate SMEs in Thailand are shown additionally in Table 1. By amount of the transfer fee, there is found that in the eastern region of Thailand, the 38.45% is displayed as the biggest volume of real estate SMEs transaction.¹⁶

Table 1.

The real estate SMEs in Thailand.

	The real estate SMEs
	Land				Buildings			Transfer fee (million Baht) (%)
Region	Land leasing	Single house	Twin house	Town house	Commercial building	Horizontal	Vertical	Transfer fee (million Baht) (%)
East	133	4,175	3,481	14,236	275	33,566	8,335	49,559 (38.45%)
South	137	547	450	954	158	32,623	2,799	26,471 (20.53%)
North	447	2,910	586	1,816	238	21,228	1,942	22,808 (17.69%)
Central	311	1,403	766	1,602	252	5,815	1,046	15,321 (11.88%)
Northeast	359	3,378	1,051	1,288	163	36,140	418	14,753 (11.45%)

Source: The real estate information center.¹⁶

At the present, more competitions, changes, and uncertainty, these matters have influenced for an organization that needs to generate a good operational performance. Adaptation of business organizations is very important to perform gradually and effectively.¹⁷ The major point is to respond to customers with the high quality of services and products which meet beyond expectations of customers.^18
–20 Celuch et al.²¹ indicated that a business organization, that strongly kept market emphasis and learning orientation, could make more added value to an organization and also increase more operational performance. In addition, factors of market and learning orientation were closely related to innovativeness and played significant roles to enhance operational performance.²² Narver and Slater²³ found that market orientation behavior positively related to profits, and the strategy that focused on a customer first was a key point because of operational performance enhancement. Moreover, other studies have been indicated that market orientation behavior that relates to innovativeness²⁴ of agencies, creative ideas, and brain storming, has affected to operational performance of organizations.¹⁰

Not only market orientation behavior but also learning orientation behavior of organizations is a key factor for the organizational success, and an organization should focus on learning orientation behavior.²⁵ Therefore, entrepreneurs should always pursue the relevant knowledge to determine directions and activities of using completed organization resources affecting the increased performance of market orientation and competitive success in the long term.²⁶ Internal learning organization is extremely necessary because an organizational existence within changing environments has issued at all times. Thus, learning orientation behavior is a good way to make greatly operational performance of business organizations.²⁷ Additionally, innovativeness is a part of organizational strategies to achieve gracefully operational performance.^28
–30 Innovativeness is a competitive business game of organizations in the 21st century including the service sector SMEs,¹² and innovativeness is also an intermediary between market orientation and learning orientation that has been influencing on operational performance of business organizations.⁸

Under the competitive environment conditions, a critical element as a core strategic component is addressed within the notion of market orientation in order to driving market achievement and firm’s ability to operate superior than its competitors.⁸ In consideration of the foundation in marketing theory, market orientation has been developing speedily over recent years into two sides as a set of behavioral activities and organizational culture.³¹ In the nature of establishing firm’s competitive advantage, to serve rapidly changing consumer needs and wants, and customer satisfaction toward building firm performance or operational performance, it is the major role of market orientation.³² According to Mahmoud et al.,⁸ they have mentioned into the previous studies which revealed two sides of findings between market orientation and operational performance. For instance, some studies found the direct relationship of them, however, other studies met either negative or non-significant relationship. As they mentioned above, the findings are found in both developed and developing countries. It is reasonable for Thailand, a developing country, to investigate and examine the impact of market orientation and operational performance.

Learning orientation is a part considered in knowledge-based resource capability that contributes to effective innovation and supports operational performance of a firm^33

–39 importantly, in previous studies, the relationship among market orientation, learning orientation, innovativeness and operational performance disclose different. By the study of Keskin,¹² market orientation impacts positively on firm learning orientation. On the other hand, Baker and Sinkula⁴⁰ stated that learning orientation has moderated between market orientation and organizational performance. Han et al.⁴¹ have argued that innovation acts as a mediator between market orientation and organizational performance. Additionally, Martinez et al.⁴² have argued that there is no evidence of the positive influence of market orientation on innovation. Moreover, Long,⁴³ Pett and Wolff,⁴⁴ Zhang and Bruning,⁴⁵ and Hurley and Hult⁴⁶ have summarized that learning orientation affected positively to market orientation. While the study of Jaworski and Kohli,³¹ it said that the role of market orientation could be both of antecedents and consequences.

Previous studies investigated above, the different roles of factors such as market orientation, learning orientation, innovativeness and operational performance have to be examined for clearly understanding particular in the present research.

For this study, the researcher has focused on four variables:

Variable of market orientation (MO), concepts of Narver and Slater,²³ Mostafa et al.,²⁴ Subagja et al.,⁴⁷ were described that the market orientation was the major key that influenced on the goal achievement of organizations by emphasizing passion of customers, requirement of a target market, and satisfaction of customers that took performance over competitors. In addition, Kotler and Keller⁴⁸ argued that the market orientation was accepted in the strategy management of modern marketing that emphasized to services, customers, competitors, operational cooperation of sectors within an organization.

Variable of learning orientation (LO), concepts of Subagja et al.,⁴⁷ Beneke et al.,⁴⁹ Baker and Sinkula,⁴⁰ Wang and Ahmed,⁵⁰ were explained that learning was a resource that provided the most value for organizations to keep operational performance and competitive advantages. It was comprised commitment of learning, shared visions and objectives, open-mindedness, and shared knowledge in an organization.

Variable of innovativeness (IN), concepts of Subagja et al.,⁴⁷ Greco et al.,⁵¹ Arshad et al.,⁵² Onag et al.,⁵³ were found that innovativeness of an organization was an overall ability of an organization to introduce new products to the markets or to seek a new market with merging strategies, innovativeness behaviors and processes.²⁸ It consisted of opening up to new ideas, product and service innovativeness,²⁴ and process innovativeness.

Variable of operational performance (OP), concepts of Falahat et al.,¹¹ Subagja et al.,⁴⁷ Girod and Whittington,⁵⁴ Kohli et al.,⁵⁵ have employed that operational performance is business investment returns in various terms including growth in sales, profitability, and market share.

Research hypotheses

According to relationship between market orientation and operational performance,^{47,49,56
–58} there is found that market orientation has indirectly influenced on operational performance via learning orientation.^47,49,59 Market orientation has indirectly influenced on operational performance via innovativeness.^{8,12,24,47,59} Moreover, market orientation has indirectly influenced on operational performance via learning orientation and innovativeness.^{10,47,51,59,60} From these findings, the hypotheses are able to propose as follows:

H1A: Market orientation has influenced on operational performance of the real estate business.

H1B: Market orientation has influenced on innovativeness.

H1C: Market orientation has influenced on learning orientation.

According to relationship between learning orientation and operational performance, there is found that learning orientation has directly influenced on operational performance.^{14,26,27,47,49,59,60} In addition, learning orientation has indirectly influenced on operational performance via innovativeness.^{12,14,47,59,60} From these previous studies, the researcher is able to define hypotheses as follows:

H2A: Learning orientation has influenced on operational performance of the real estate business.

H2B: Learning orientation has influenced on innovativeness.

According to relationship between innovativeness and operational performance, there is found that innovativeness has directly influenced on operational performance.^{9,10,12,13,28,47,51,56,59
–61} From this result, the hypothesis is set as follow:

H3A: Innovativeness has influenced on operational performance of the real estate business. Figure 1

Figure 1.

Hypotheses definition.^{8
–10,12
–14,24,26,27,47,49,51,56

–61}

Methodology

Population and sample

Population for this study is defined into the real estate entrepreneurs of the service sector SMEs in Thailand comprising five regions: the northern region, the northeastern region, the central region, the eastern region, and the southern region.⁶² Under the umbrella of operation of the real estate business among regions, there are no difference of them and operated under the same laws and regulations belonging to the Department of Lands, Ministry of Interior, Thailand.

Sample size for this study with using SEM, it was estimated initially with number of observed variables multiplied by 15. So that, 37 × 15 = 555 samples was firstly identified. To make sure on this issue, it was certified by the suggestion of Hair et al.⁶³ after prior data analysis, there was some with lower communalities and having fewer than three measured items in each construct. Following their suggestion, the minimum at 500 samples was reasonable.

Multi-stage random sampling was employed in this study for such five regions.⁶⁴ The first step, the researcher used stratified sampling method to select one province that registered the maximum number of transferring real estate ownerships in each region, the total were in five provinces: Chiangmai, Nakhon Ratchasima, Ayutthaya, Chonburi, and Phuket. The second step, the sample was selected randomly from the SMEs real estate entrepreneurs by using quota sampling method. To eliminate the missing data and any further incompleteness, the total 600 questionnaires were distributed by mail. With the helps and cooperation of SMEs local network in collecting data, finally, 555 completed questionnaires were returned.

To account for the differences among real estate business of all parts of Thailand, company scale, financial and economic condition were forced to be the control variables. Following the suggestion of Wang and Hsu,⁶⁵ the author has identified the control variables within only the definition of real estate SMEs in Thailand previously.

Tool for collecting data and analysis

The questionnaire was used as the research tool to survey data among entrepreneurs of real estate business in the province that registered the maximum number of transferring real estate ownerships. This survey was utilized to define variables which influenced on operational performance of REB including market orientation, learning orientation, innovativeness, and operational performance of REB and evaluated within the five-level rating scale and further analyzed with AMOS version 26.

To construct a questionnaire, the researcher has examined both of validity and reliability. The content validity was tested by five experts based on the index of item objective congruence (IOC). For the validity test, all items were in greater than 0.5 of IOC.^64,66 For the reliability test, all items were found that α-coefficient was between .738 and .899 (α-coefficient > .700);^67,68 factor loading was between .560 and .951; composite reliability (CR) of latent factors was between .769 and .909 (CR > .700);^63,69 average variance extracted (AVE) was between .502 and .833 (AVE > .500);^70,71 and maximum shared variance (MSV) was between .403 and .698 (all of MSV < AVE).⁷⁰

The abbreviations were presented instead of relevant variables: market orientation (MO), learning orientation (LO), innovativeness (IN), operational performance of real estate business (OP), inter-functional coordination (IF), competitor orientation (CP), customer orientation (CM), shared vision (SV), commitment of learning (CT), open-mindedness (OM), product and service innovativeness (PD), opening up to new ideas (ON), process innovativeness (PC), growth in sales (GI), market share (MK), and profitability (PF), shown in Table 2.

Table 2.

Reliability, convergent validity, and discriminant validity for the measurement model.

Second latent	Latent variable	Observed variable	Factor loading	Reliability	CR (>.70)	AVE (>.50)	MVS (MVS < AVE)
MO	CP	CP1	.796	.794	.880	.648	.501
		CP2	.870
		CP3	.837
		CP4	.709
	IF	IF1	.848	.880	.904	.704	.622
		IF2	.842
		IF3	.905
		IF4	.753
	CM	CM1	.747	.878	.800	.502	.456
		CM2	.794
		CM3	.560
		CM4	.618
LO	SV	SV1	.751	.875	.845	.524	.432
		SV2	.709
		SV3	.595
		SV4	.815
		SV5	.730
	CT	CT1	.782	.864	.868	.622	.553
		CT2	.813
		CT3	.739
		CT4	.818
	OM	OM1	.770	.770	.769	.526	.403
		OM2	.686
		OM3	.717
IN	ON	ON1	.938	.738	.788	.657	.511
		ON2	.659
	PD	PD1	.825	.817	.830	.710	.630
		PD2	.860
	PC	PC1	.951	.899	.909	.833	.698
		PC2	.873
OP	GI	GI1	.810	.812	.814	.686	.541
		GI2	.846
	PF	PF1	.909	.839	.856	.749	.644
		PF2	.820
	MK	MK1	.866	.886	.886	.723	.657
		MK2	.904
		MK3	.775

Results

Confirmatory factor analysis on the measurement model, there were found that (1) MO was measured by three observed variables. The most factor loading was IF, there were CP and CM respectively; (2) LO was measured by three observed variables. The most factor loading was CT, there were SV and OM respectively; (3) IN was measured by three observed variables. The most factor loading was PC, there were ON and PD respectively; (4) OP was measured by three observed variables. The most factor loading was PF, there were MK and GI respectively.

For empirical data consistency, the chi-squared/df test equaled .835 which was less than 2.^69,72 The p-value of chi-squared equaled .993. Goodness of fit index (GFI) equaled .960 which was greater than .90.^73,74 Adjusted goodness of fit index (AGFI) equaled .945 which was greater than .90.^73,74 Comparative fit index (CFI) equaled 1.000 which was greater than .90.⁷² Root mean square error of approximation (RMSEA) equaled .000 which was less than .08.^75

–78 Therefore, these results were indicated that the causal relationship model of factors that influenced on OP had been consistent with the empirical data, shown in Table 3 and Figure 2.

Table 3.

Summary of the structural model fit.

Fit index	Recommended value	Observed value
χ²/df	≤ 2 (Kline⁷²; Schumacker and Lomax⁶⁹)	.853
p-value	≥ .05 (Kline⁷²; Schumacker and Lomax⁶⁹)	.993
GFI	≥ .90 (Afthanorhan and Ahmad⁷³; Hooper et al.⁷⁴)	.960
AGFI	≥ .90 (Afthanorhan and Ahmad⁷³; Hooper et al.⁷⁴)	.945
CFI	≥ .90 (Kline⁷²)	1.000
RMSEA	≤ .08 (Pérez-Campdesuñer et al.⁷⁵; Vanichbuncha⁷⁶; Hsu et al.⁷⁷; James et al.⁷⁸)	.000

Figure 2.

The causal relationship model of factors that influenced on operational performance of REB.

The study of the causal relationship model, and consistency verification of this model and empirical data of factors that influenced on OP, there were found that the generated causal relationship model of factors that influenced on OP was firstly inconsistent with empirical data. After that, this model was modified, finally, the re-specified model was fit. It meant that there was consistent with empirical data and path coefficient test of factors that influenced on OP, shown in Table 4.

Table 4.

Results of path coefficient test of factors that influenced on operational performance of REB and consistency verification of the causal relationship model and the empirical data.

Path coefficients of latent variables	Standard estimate	Estimate	SE	CR	p	R ²	Hypothesis	Result
MO → OP	.475	1.277	.307	4.159	***	.628	H1A	Supported
LO → OP	.085	.096	.091	1.058	.290		H2A	Not supported
IN → OP	.277	.278	.079	3.543	***		H3A	Supported
MO → IN	.649	1.738	.274	6.334	***	.669	H1B	Supported
LO → IN	.190	.213	.089	2.401	*		H2B	Supported
MO → LO	.857	2.045	.204	10.030	***	.735	H1C	Supported
χ²/df = .835, p = .993, GFI = .960, AGFI = .945, CFI = 1.000, RMSEA = .000

* Significant level of .05.

** Significant level of .01.

*** Significant level of .001.

From Table 4, results of path coefficient test of factors that influenced on operational performance of REB, there were found that:

Path coefficient of factors that influenced on OP was between .085 and .475. MO has been the highest path coefficient, and LO has been the lowest path coefficient. Path coefficient of MO and IN have influenced on OP with a statistical significance (p < .001) whereas LO has not influenced on OP. Thus, H1A and H3A were supported, but H2A was not supported.

For MO, path coefficient to IN was .649 with a statistical significance (p < .001), and for LO, path coefficient to IN was .190 with a statistical significance (p < .05). Thus, both of H1B and H2B were supported.

For MO, path coefficient to LO was .857 with a statistical significance (p < .001). Thus, H1C was supported.

R ² was between .628 and .735. LO has been the highest path coefficient. Thus, there was indicated that antecedent variables (MO, LO, IN) were able to explain the causal relationship model of them that influenced on the consequence variable (OP) at 62.80%.

From Table 5, results of direct, indirect, and total effects of factors that influenced on OP, there were indicated that:

MO has directly influenced on LO (DE = .857, TE = .857); MO has directly and indirectly influenced on IN via the LO mediator variable (DE = .649, IE = .163, TE = .812); and MO has directly and indirectly influenced on OP (DE = .475, IE = .298, TE = .773).

LO has directly influenced on IN (DE = .190, TE = .190), but LO has not influenced on OP (DE = .085, IE = .053, TE = .138).

IN has directly influenced on OP (DE = .277, TE = .277).

Table 5.

Direct, indirect, and total effects of factors that influenced on operational performance of REB.

Effects from	Direct effect (DE)	Indirect effect (IE)	Total effect (TE)
MO to LO	.857***	—	.857
MO to IN	.649***	.163	.812
MO to OP	.475***	.298	.773
LO to IN	.190*	—	.190
LO to OP	.085	.053	.138
IN to OP	.277***	—	.277

Discussion

MO has directly and indirectly influenced on OP, that such finding has conformed to the study of Keskin,¹² Na et al.,⁵⁶ Kajalo and Lindblom,⁷⁹ and Mahmoud.⁸⁰ In addition, MO has directly and indirectly influenced on IN.^{8,10,12,24,59,60} These results are indicated that Thai real estate business needs to extremely emphasize the market orientation. Relationships of market orientation, learning orientation, and innovativeness are actually important to define strategies, management, and market for businesses that conform to the study of Rhee et al.,¹⁰ they have found that the salient feature of real estate business has to focus on learning orientation played as the mediator variable between market orientation and innovativeness in order to enhance operational performance of business. Therefore, there should strongly emphasize market orientation and learning orientation to increase innovativeness which influences on operational performance of real estate business.

LO has directly influenced on IN that such finding has related to the study of Phasuk,¹⁴ Lopez et al.,²⁶ Martinette and Leeson,²⁷ Baker and Sinkula,⁴⁰ Na et al.,⁵⁶ they have found that for the service business, the learning orientation has extremely related to innovativeness of business because of establishing direct interaction between buyers and sellers in period of service times that it is the heart of the service sector. In addition, this result is supported with the study of Nurhasanah and Murwatiningsih,⁵⁹ they have found that observed variables that are significant with learning orientation, and being the inter-functional coordination and the shared vision within an organization to promote new ideas and performance of business. Therefore, the facility management in an organization is going to encourage learning orientation which influences on operational performance of real estate business driven.

IN has directly influenced on OP that such finding has conformed to the study of Salim and Sulaiman,⁹ Rhee et al.,¹⁰ Keskin,¹² Leekpai et al.,¹³ Weiss and Legrand,²⁸ Na et al.,⁵⁶ Zayed and Alawad,⁶⁰ they have found that in the developing countries, innovativeness of business organization has directly influenced on operational performance of business organization. In addition, this result is supported with the study of Leekpai et al.,¹³ there is found that innovative promotion, market orientation roles, and learning orientation in an organization have to usually advocate innovativeness of business because it has positively influenced on operational performance of business.⁶¹ Moreover, an organization should be continuously promoted an innovative creation in order to still increase operational performance of business.

LO has non-significant statistically influenced on OP. It could be explained by the nature of REB in Thailand. LO is particularly defined for the present research as commitment of learning, shared visions and objectives, open-mindedness, and shared knowledge in an organization. Unfortunately, the nature of these activities is dominantly regulated by the Department of Land, Thailand. Moreover, doing REB business is mainly in hand of the specific investors. As a result, LO has not much opportunity to be distributed in generally. It should be further with the cooperation between government and entrepreneurs in REB, there is then the empirical evidences occurred between LO and OP in Thailand (see more in Khumpaisal,⁸¹ Rattanaprichavej et al.⁸²).

Conclusion

This research has emphasized to the study and consistency verification of the causal relationship model that influences on operational performance of REB in Thailand. This generated model is indicated that market orientation has directly and indirectly influenced on operational performance of REB, and innovativeness has directly influenced on operational performance of REB whereas learning orientation has not influenced on operational performance of REB. However, learning orientation is as the mediator variable between market orientation and innovativeness. For each antecedent variable, market orientation has activated into three aspects: inter-functional coordination, competitor orientation, and customer orientation. Learning orientation has activated into three aspects: shared vision, commitment of learning, and open-mindedness. Innovativeness has activated into three aspects: opening up to new ideas, product and service innovativeness, and process innovativeness. In addition, operational performance of REB has activated three aspects: growth in sales, market share, and profitability. Therefore, governmental and non-governmental agencies that concern with REB are able to apply these results as concepts to promote modernly operational performance for current change supports. Especially, REB entrepreneurs are able to take such concepts of marketing orientation, learning orientation, and innovativeness to enhance level of services and operational performance via relevant activities and projects such as training to promote satisfaction of customers, knowledge management in an organization, supporting the vocational training, offering rewards to outstanding personnel, using modern and suitable technologies, facility management to encourage more operational performance, and so on. Moreover, these results are able to be also adaptable implementation to other service businesses.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Funding

The author(s) received no financial support for the research,authorship,and/or publication of this article.

ORCID iD

Irada Phorncharoen

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Influence of market orientation,learning orientation,and innovativeness on operational performance of real estate business

Abstract

Keywords

Introduction

Literature review

Research hypotheses

Methodology

Population and sample

Tool for collecting data and analysis

Results

Discussion

Conclusion

Footnotes

Declaration of conflicting interests

Funding

ORCID iD

References