SERVITIZATION AND ORGANIZATIONAL PERFORMANCE IN THE MACHINERY AND EQUIPMENT SECTOR

SOUZA JUNIOR, WESLEY CANEDO DE; TORRES JÚNIOR, NOEL; MIYAKE, DARIO IKUO

doi:10.1590/S0034-759020180504

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ARTICLES • Rev. adm. empres. 58 (5) • Sep-Oct 2018 • https://doi.org/10.1590/S0034-759020180504 copy

SERVITIZATION AND ORGANIZATIONAL PERFORMANCE IN THE MACHINERY AND EQUIPMENT SECTOR

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

The role of manufacturing in value chains has become less dominant given the trend of stagnating demand, commoditization of products, and declining profitability. Confronted with this challenging scenario, a growing number of companies seek to add value to their businesses by adopting the approach of "servitization" (offering product-service solutions). However, literature on this subject is divided on the effectiveness of this approach since the intended outcome is not always achieved (service paradox). As such, this study quantitatively evaluates this relationship in manufacturing firms within the machinery and equipment industry. Data on different service categories developed by these firms and their corresponding impacts were collected. It was verified that there is a positive and significant relationship between the majority of these service categories and organizational performance, which indicates that identifying and developing a consistent service bundle may serve as an effective servitization strategy.

KEYWORDS:
Servitization; Organizational performance; Service paradox; Machinery and Equipment; Product-service system

First-order Construct	Abbreviation	Definition
Basic Services (SB)^a a Parida et al. (2014)	CB	Cost-benefit calculation services (ex.: helping the customer choose the product with the best cost-benefit ratio for their case)
	CONS	Consulting services for the customer and support by telephone
	INFO	Written information material (ex.: manuals)
	TREI	Technical training services for users
Maintenance Services (SM)^a a Parida et al. (2014)	MANUT	Maintenance services (ex.: corrective, preventive)
	UPG	Product upgrading services (ex.: updates, upgrades)
	SUP	Technical support services for similar products by other manufacturers
Research and Development Services (SPD)^a a Parida et al. (2014)	MANUF	Services for analyzing product manufacturability (ex.: calculation and optimization of the design for products that are easier to manufacture)
	AP	Services for analyzing problems (ex.: a system that monitors operation data of the product sold to the customer and alerts when potential problems might occur)
	VIAB	Feasibility study services (ex.: feasibility analysis for personalized products requested by the customer)
	DESEN	Prototype design and development services
	PESQ	Research services (ex.: study and development of new Technologies, products)
Functional Services (SF)^a a Parida et al. (2014)	OPC	Service for operating customers' process (ex.: The manufacturer uses the product that it produces to operate the customer's process, but does not sell it. The product is only part of the solution.)
Functional Services (SF)^a a Parida et al. (2014)	OPV	Service for operating the product sold to the customer (ex.: The manufacturer sells the product that it produces to the customer but operates the customer's process using this purchased product.)
Servitization^b b Oliva & Kallenberg (2003)	GERAL	Company's level of service orientation considering that the main objective of a "completely service-oriented" firm is to offer services to its customers, with the product being just a part of the solution.

First-order construct	Abbreviation	Indicator	Nature of indicator	Referential frameworks that associate the Indicator with servitization
Financial performance (DES_FIN)	DLG	General profitability	Financial result measure	Wise & Baumgartner (1999)Wise, R., & Baumgartner, P. (1999). Go downstream: The new profit imperative in manufacturing. Harvard Business Review, 77(5), 133-141.; Allmendinger & Lombreglia (2005)Allmendinger, G., & Lombreglia, R. (2005, October). Four strategies for the age of smart services. Harvard Business Review, 83, 131-145.; Karlsson (2007)Karlsson, U. (2007). Service Based manufacturing strategies implication for product development, production and service operations in global companies. POMS College of Service Operations and EurOMA Conference. London, UK.; Neely (2008)Neely, A. (2008). Exploring the financial consequences of the servitization of manufacturing. Operations Management Research, 1(2), 103-118.; Prester (2011)Prester, J. (2011). Servitization as a strategy for survival: Evidence from a small European country. 18th International Annual EurOMA Conference. Cambridge, UK.; Kastkalli & Looy (2013)Kastalli, I. V., & Looy, B. Van. (2013). Servitization: Disentangling the impact of service business model innovation on manufacturing firm performance. Journal of Operations Management, 31(4), 169-180..
	DRA	Return on assets (net profit/total assets)	Financial result measure	Wise & Baumgartner (1999)Wise, R., & Baumgartner, P. (1999). Go downstream: The new profit imperative in manufacturing. Harvard Business Review, 77(5), 133-141.; Lindström (2014)Lindström, J. (2014). A model for value-based selling: Enabling corporations to transition from products and services towards further complex business models. Journal of Multi Business Model Innovation and Technology, 2(1), 67-98. .
	DRENT	Net profitability (net profit/total investment)	Financial result measure	Wise & Baumgartner (1999)Wise, R., & Baumgartner, P. (1999). Go downstream: The new profit imperative in manufacturing. Harvard Business Review, 77(5), 133-141.; Goffin (1999)Goffin, K. (1999). Customer support. International Journal of Physical Distribution & Logistics Management, 29(6), 374-398.; Allmendinger & Lombreglia (2005)Allmendinger, G., & Lombreglia, R. (2005, October). Four strategies for the age of smart services. Harvard Business Review, 83, 131-145..
Operational performance (DES_OP)	DPM	Market share	External operational effectiveness measure	Goffin (1999)Goffin, K. (1999). Customer support. International Journal of Physical Distribution & Logistics Management, 29(6), 374-398.; Vandermerwe & Rada (1988)Vandermerwe, S., & Rada, J. (1988). Servitization of business: Adding value by adding services. European Management Journal, 6(4), 314-324.
	DPO	Operational productivity	Internal measure of operational efficiency and effectiveness	Neely (2008)Neely, A. (2008). Exploring the financial consequences of the servitization of manufacturing. Operations Management Research, 1(2), 103-118.; Bascavusoglu-Moreau & Tether (2011)Bascavusoglu-Moreau, E., & Tether, B. (2011). Servitization, survival and productivity: A longitudinal study of UK manufacturing firms. DRUID 2011 - Innovation, Strategy, and Structure - Organizations, Institutions, Systems and Regions. Copenhagen, Denmark.; Baines & Lightfoot (2012)Baines, T., Bigdeli, A. Z., Bustinza, O. F., Shi, V. G., Baldwin, J., & Ridgway, K. (2017). Servitization: Revisiting the state-of-the-art and research priorities. International Journal of Operations and Production Management, 37(2), 256-278.
	DVEND	Sales volume	External operational effectiveness measure	Goffin (1999)Goffin, K. (1999). Customer support. International Journal of Physical Distribution & Logistics Management, 29(6), 374-398.; Brax (2005)Brax, S. (2005). A manufacturer becoming service provider: Challenges and a paradox. Managing Service Quality: An International Journal, 15(2), 142-155.; Prester (2011)Prester, J. (2011). Servitization as a strategy for survival: Evidence from a small European country. 18th International Annual EurOMA Conference. Cambridge, UK.; Kastalli & Looy (2013)Kastalli, I. V., & Looy, B. Van. (2013). Servitization: Disentangling the impact of service business model innovation on manufacturing firm performance. Journal of Operations Management, 31(4), 169-180..

Construct	Cronbach's Alpha	Composite reliability
SERV	1.000	1.000
SB	0.658	0.793
SM	0.433	0.694
SPD	0.812	0.867
SF	0.736	0.880
DES	0.899	0.923
DES_FIN	0.901	0.938
DES_OP	0.786	0.875

Latent Variable	Indicator	Outer loading	Communality
SB	CB	0.61	0.372
	CONS	0.786	0.618
	INFO	0.718	0.515
	TREI	0.68	0.462
SM	MANUT	0.468	0.219
	UPG	0.874	0.763
	SUP	0.598	0.357
SPD	MANUF	0.618	0.381
	AP	0.847	0.718
	VIAB	0.814	0.663
	DESEN	0.676	0.457
	PESQ	0.791	0.626
SF	OPC	0.842	0.709
SF	OPV	0.929	0.862
DES_FIN	DLG	0.912	0.831
	DRA	0.903	0.815
	DRENT	0.926	0.858
DES_OP	DPM	0.848	0.719
	DPO	0.849	0.721
	DVEND	0.814	0.662

Construct	Average Variance Extracted (AVE)
SERV	1.000
SB	0.492
SF	0.786
SM	0.446
SPD	0.569
DES	0.667
DES_FIN	0.835
DES_OP	0.701

Construct	Indicator	AVE		Composite Reliability		Adjusted R²
Construct	Indicator	Before	After	Before	After	Before	After
SB	CB	0.492	0.567	0.793	0.797	0.345	0.352
SB	TREI	0.492	0.550	0.793	0.784	0.345	0.355
SM	MANUT	0.446	0.582	0.694	0.729	0.345	0.357
SM	SUP	0.446	0.591	0.694	0.722	0.345	0.325
SPD	MANUF	0.569	0.626	0.867	0.869	0.345	0.348
SPD	DESEN	0.569	0.611	0.867	0.861	0.345	0.347

Construct	DES_FIN	DES_OP	SERV	SB	SM	SPD	SF
DES_FIN	0.914
DES_OP	0.737	0.837
SERV	0.350	0.471	1
SB	0.221	0.377	0.454	0.701
SM	0.204	0.318	0.507	0.473	0.763
SPD	0.241	0.368	0.459	0.519	0.489	0.754
SF	0.292	0.236	0.393	0.185	0.261	0.442	0.886

Construct	Tolerance	Variance Inflation Factor (VIF)
SB	0.652	1.535
SM	0.664	1.505
SPD	0.559	1.788
SF	0.798	1.254

Hypothesis	Relationship	Path coefficient	t Statistics	P-value	Evaluation
H1	SERV -> DES	0.435	3.908	.000	Significant at 1%
H2	SB -> SERV	0.223	2.239	.025	Significant at 5%
	SM -> SERV	0.268	2.581	.010	Significant at 5%
	SPD -> SERV	0.104	1.057	.290	Not Significant
	SF -> SERV	0.236	2.595	.009	Significant at 1%
H3	DES -> DES_FIN	0.942	89.608	.000	Significant at 1%
H3	DES -> DES_OP	0.921	52.084	.000	Significant at 1%

Construct	Coefficient of Determination R²	Evaluation by Hair et al.'s Criteria (2014)Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks, USA: Sage Publications, Inc.	Evaluation by Chin's Criteria (1998)Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In Marcoulides, G.A. (Ed.). Modern methods for business research (pp. 295-358). Mahwah, USA: Lawrence Erlbaum Associates, Inc.
SERV	0.374	Weak	Moderate
DES	0.190	Weak	Weak
DES_FIN	0.888	Substantial	Substantial
DES_OP	0.848	Substantial	Substantial

Performance Indicator		Proportion of companies that agree that performance increases with servitization				χ ²	P-Value	Cramer's V	Result of the Marascuilo Procedure
Performance Indicator		Strongly or fully service-oriented firms (Group A)	Reasonably service-oriented firms (Group B)	Poorly service-oriented firms (Group C)	Entire sample	χ ²	P-Value	Cramer's V	Result of the Marascuilo Procedure
Financial Performance	Overall Profitability	36/42	24/35	7/15	67/92	9.03	.0109	0.31	Significant difference between Groups A and C
	Overall Profitability	85.7%	68.6%	46.7%	72.8%		< .05	0.31	Significant difference between Groups A and C
	Return on Assets	30/42	17/35	5/15	52/92	7.98	.0185	0.29	Significant difference between Groups A and C
	Return on Assets	71.4%	48.6%	33.3%	56.5%		< .05	0.29	Significant difference between Groups A and C
	Net Profitability	36/42	25/35	7/15	68/92	8.92	.0116	0.31	Significant difference between Groups A and C
	Net Profitability	85.7%	71.4%	46.7%	73.9%		< .05	0.31	Significant difference between Groups A and C
Operational Performance	Sales Volume	38/42	23/35	7/15	68/92	12.97	.0015	0.38	Significant difference between Groups A and B and Groups A and C
	Sales Volume	90.5%	65.7%	46.7%	73.9%		< .01	0.38
	Operational Productivity	36/42	20/35	6/15	62/92	13.21	.0014	0.38	Significant difference between Groups A and B and Groups A and C
	Operational Productivity	85.7%	57.1%	40.0%	67.4%		< .01	0.38
	Market Share	37/42	24/35	8/15	69/92	8.37	.0152	0.30	Significant difference between Groups A and C
	Market Share	88.1%	68.6%	53.3%	75.0%		< .05	0.30	Significant difference between Groups A and C

Relationship between constructs	Path coefficient	t Statistics	p-Value	Evaluation
SERV -> DES_FIN	0.410	3.892	.000	Significant at 1%
SERV -> DES_OP	0.401	3.833	.000	Significant at 1%
SB -> DES	0.097	1.810	.070	Significant at 10%
SB -> DES_FIN	0.092	1.806	.071	Significant at 10%
SB -> DES_OP	0.090	1.795	.073	Significant at 10%
SM -> DES	0.116	2.186	.029	Significant at 5%
SM -> DES_FIN	0.110	2.186	.029	Significant at 5%
SM -> DES_OP	0.107	2.174	.030	Significant at 5%
SPD -> DES	0.045	0.952	.341	Not Significant
SPD -> DES_FIN	0.043	0.950	.342	Not Significant
SPD -> DES_OP	0.042	0.946	.344	Not Significant
SF -> DES	0.103	2.119	.034	Significant at 5%
SF -> DES_FIN	0.097	2.110	.035	Significant at 5%
SF -> DES_OP	0.095	2.100	.036	Significant at 5%

Performance Indicator		Proportion of companies that agree that performance increases with servitization				χ ²	p-Value
Performance Indicator		Up to 19 employees (Group A)	20 to 99 employees (Group B)	100 to 499 employees (Group C)	Entire sample	χ ²	p-Value
Financial	Overall Profitability	27/38	33/45	7/9	67/92	0.18	.9150
	Overall Profitability	71.1%	73.3%	77.8%	72.8%	0.18	.9150
	Return on Assets	22/38	24/45	6/9	52/92	0.59	.7437
	Return on Assets	57.9%	53.3%	66.7%	56.5%	0.59	.7437
	Net Profitability	27/38	34/45	7/9	68/92	0.29	.8633
	Net Profitability	71.1%	75.6%	77.8%	73.9%	0.29	.8633
Operational	Sales Volume	26/38	37/45	5/9	68/92	3.78	.1512
	Sales Volume	68.4%	82.2%	55.6%	73.9%	3.78	.1512
	Operational Productivity	24/38	32/45	6/9	62/92	0.60	.7425
	Operational Productivity	63.2%	71.1%	66.7%	67.4%	0.60	.7425
	Market Share	24/38	37/45	8/9	69/92	5.02	.0813^* * Significant difference at 10%
	Market Share	63.2%	82.2%	88.9%	75.0%	5.02	.0813^* * Significant difference at 10%

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